IDEAS home Printed from https://ideas.repec.org/r/bla/jorssb/v67y2005i5p768-768.html
   My bibliography  Save this item

Addendum: Regularization and variable selection via the elastic net

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Tutz, Gerhard & Pößnecker, Wolfgang & Uhlmann, Lorenz, 2015. "Variable selection in general multinomial logit models," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 207-222.
  2. Li, W. & Fok, D. & Franses, Ph.H.B.F., 2019. "Forecasting own brand sales: Does incorporating competition help?," Econometric Institute Research Papers EI2019-35, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  3. Özen, Kadir & Yıldırım, Dilem, 2021. "Application of bagging in day-ahead electricity price forecasting and factor augmentation," Energy Economics, Elsevier, vol. 103(C).
  4. Felix Pretis & Lea Schneider & Jason E. Smerdon & David F. Hendry, 2016. "Detecting Volcanic Eruptions In Temperature Reconstructions By Designed Break-Indicator Saturation," Journal of Economic Surveys, Wiley Blackwell, vol. 30(3), pages 403-429, July.
  5. Josh N. Vo & Yi-Mi Wu & Jeanmarie Mishler & Sarah Hall & Rahul Mannan & Lisha Wang & Yu Ning & Jin Zhou & Alexander C. Hopkins & James C. Estill & Wallace K. B. Chan & Jennifer Yesil & Xuhong Cao & Ar, 2022. "The genetic heterogeneity and drug resistance mechanisms of relapsed refractory multiple myeloma," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
  6. Quoc Tran-Dinh, 2019. "Proximal alternating penalty algorithms for nonsmooth constrained convex optimization," Computational Optimization and Applications, Springer, vol. 72(1), pages 1-43, January.
  7. Oxana Babecka Kucharcukova & Jan Bruha, 2016. "Nowcasting the Czech Trade Balance," Working Papers 2016/11, Czech National Bank.
  8. Victor Chernozhukov & Christian Hansen & Yuan Liao, 2015. "A lava attack on the recovery of sums of dense and sparse signals," CeMMAP working papers 56/15, Institute for Fiscal Studies.
  9. Anurag Satpathi & Parul Setiya & Bappa Das & Ajeet Singh Nain & Prakash Kumar Jha & Surendra Singh & Shikha Singh, 2023. "Comparative Analysis of Statistical and Machine Learning Techniques for Rice Yield Forecasting for Chhattisgarh, India," Sustainability, MDPI, vol. 15(3), pages 1-18, February.
  10. Wenjia Wang & Yi-Hui Zhou, 2022. "A Double Penalty Model for Ensemble Learning," Mathematics, MDPI, vol. 10(23), pages 1-23, November.
  11. Tomohiro Ando & Naoya Sueishi, 2019. "On the Convergence Rate of the SCAD-Penalized Empirical Likelihood Estimator," Econometrics, MDPI, vol. 7(1), pages 1-14, March.
  12. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
  13. Freire, Gustavo, 2021. "Tail risk and investors’ concerns: Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
  14. Sierra A. Bainter & Thomas G. McCauley & Mahmoud M. Fahmy & Zachary T. Goodman & Lauren B. Kupis & J. Sunil Rao, 2023. "Comparing Bayesian Variable Selection to Lasso Approaches for Applications in Psychology," Psychometrika, Springer;The Psychometric Society, vol. 88(3), pages 1032-1055, September.
  15. Yongxia Zhang & Qi Wang & Maozai Tian, 2022. "Smoothed Quantile Regression with Factor-Augmented Regularized Variable Selection for High Correlated Data," Mathematics, MDPI, vol. 10(16), pages 1-30, August.
  16. Seán Schmitz & Sophia Becker & Laura Weiand & Norman Niehoff & Frank Schwartzbach & Erika von Schneidemesser, 2019. "Determinants of Public Acceptance for Traffic-Reducing Policies to Improve Urban Air Quality," Sustainability, MDPI, vol. 11(14), pages 1-16, July.
  17. Jionghua Wang & Bo Huang & Ting Zhang & Hung Wong & Yifan Huang, 2018. "Impact of Housing and Community Conditions on Multidimensional Health among Middle- and Low-Income Groups in Hong Kong," IJERPH, MDPI, vol. 15(6), pages 1-14, May.
  18. Kockerols, Thore & Kok, Christoffer, 2019. "Leaning against the wind: macroprudential policy and the financial cycle," Working Paper Series 2223, European Central Bank.
  19. Hou-Tai Chang & Ping-Huai Wang & Wei-Fang Chen & Chen-Ju Lin, 2022. "Risk Assessment of Early Lung Cancer with LDCT and Health Examinations," IJERPH, MDPI, vol. 19(8), pages 1-12, April.
  20. Panopoulou, Ekaterini & Vrontos, Spyridon, 2015. "Hedge fund return predictability; To combine forecasts or combine information?," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 103-122.
  21. Wentao Qu & Xianchao Xiu & Huangyue Chen & Lingchen Kong, 2023. "A Survey on High-Dimensional Subspace Clustering," Mathematics, MDPI, vol. 11(2), pages 1-39, January.
  22. Eickmeier, Sandra & Ng, Tim, 2011. "Forecasting national activity using lots of international predictors: An application to New Zealand," International Journal of Forecasting, Elsevier, vol. 27(2), pages 496-511, April.
  23. Kuppenheimer, Gregory & Shelly, Stuart & Strauss, Jack, 2023. "Can machine learning identify sector-level financial ratios that predict sector returns?," Finance Research Letters, Elsevier, vol. 57(C).
  24. Alexander M. Chinco & Adam D. Clark-Joseph & Mao Ye, 2017. "Sparse Signals in the Cross-Section of Returns," NBER Working Papers 23933, National Bureau of Economic Research, Inc.
  25. Margherita Giuzio, 2017. "Genetic algorithm versus classical methods in sparse index tracking," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 40(1), pages 243-256, November.
  26. Anwen Yin, 2022. "Does the kitchen‐sink model work forecasting the equity premium?," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 223-247, March.
  27. Liang, Chong & Schienle, Melanie, 2019. "Determination of vector error correction models in high dimensions," Journal of Econometrics, Elsevier, vol. 208(2), pages 418-441.
  28. Orestis P. Panagopoulos & Petros Xanthopoulos & Talayeh Razzaghi & Onur Şeref, 2019. "Relaxed support vector regression," Annals of Operations Research, Springer, vol. 276(1), pages 191-210, May.
  29. Liu, Yufeng & Helen Zhang, Hao & Park, Cheolwoo & Ahn, Jeongyoun, 2007. "Support vector machines with adaptive Lq penalty," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6380-6394, August.
  30. Zakariya Yahya Algamal & Muhammad Hisyam Lee, 2019. "A two-stage sparse logistic regression for optimal gene selection in high-dimensional microarray data classification," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(3), pages 753-771, September.
  31. Bienvenue Kouwaye & Fabrice Rossi & Noël Fonton & André Garcia & Simplice Dossou-Gbété & Mahouton Norbert Hounkonnou & Gilles Cottrell, 2017. "Predicting local malaria exposure using a Lasso-based two-level cross validation algorithm," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-14, October.
  32. Román Salmerón Gómez & Ainara Rodríguez Sánchez & Catalina García García & José García Pérez, 2020. "The VIF and MSE in Raise Regression," Mathematics, MDPI, vol. 8(4), pages 1-28, April.
  33. Lee, Seokho & Huang, Jianhua Z., 2013. "A coordinate descent MM algorithm for fast computation of sparse logistic PCA," Computational Statistics & Data Analysis, Elsevier, vol. 62(C), pages 26-38.
  34. Luca Insolia & Ana Kenney & Martina Calovi & Francesca Chiaromonte, 2021. "Robust Variable Selection with Optimality Guarantees for High-Dimensional Logistic Regression," Stats, MDPI, vol. 4(3), pages 1-17, August.
  35. D’Hondt, Catherine & De Winne, Rudy & Ghysels, Eric & Raymond, Steve, 2020. "Artificial Intelligence Alter Egos: Who might benefit from robo-investing?," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 278-299.
  36. Adewale Folaranmi Lukman & Jeza Allohibi & Segun Light Jegede & Emmanuel Taiwo Adewuyi & Segun Oke & Abdulmajeed Atiah Alharbi, 2023. "Kibria–Lukman-Type Estimator for Regularization and Variable Selection with Application to Cancer Data," Mathematics, MDPI, vol. 11(23), pages 1-11, November.
  37. Hunger, Sophia & Lorenzini, Jasmine, 2020. "All Quiet on the Protest Scene? Repertoires of Contention and Protest Actors During the Great Recession," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 104-127.
  38. Breinlich, Holger & Corradi, Valentina & Rocha, Nadia & Ruta, Michele & Silva, J.M.C. Santos & Zylkin, Tom, 2021. "Machine learning in international trade research - evaluating the impact of trade agreements," LSE Research Online Documents on Economics 114379, London School of Economics and Political Science, LSE Library.
  39. Pierre Pinson & Liyang Han & Jalal Kazempour, 2022. "Regression markets and application to energy forecasting," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 533-573, October.
  40. Marie Bessec, 2013. "Short‐Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 500-511, September.
  41. Miyazaki, Izuru, 2023. "Recovery of partly sparse and dense signals," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
  42. Zhang, Yan-Qing & Tian, Guo-Liang & Tang, Nian-Sheng, 2016. "Latent variable selection in structural equation models," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 190-205.
  43. Xiaoshan Li & Da Xu & Hua Zhou & Lexin Li, 2018. "Tucker Tensor Regression and Neuroimaging Analysis," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(3), pages 520-545, December.
  44. Zhong, Yan & Sang, Huiyan & Cook, Scott J. & Kellstedt, Paul M., 2023. "Sparse spatially clustered coefficient model via adaptive regularization," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
  45. Hiroki Tanabe & Ellen H. Fukuda & Nobuo Yamashita, 2023. "An accelerated proximal gradient method for multiobjective optimization," Computational Optimization and Applications, Springer, vol. 86(2), pages 421-455, November.
  46. Stefanie Hieke & Axel Benner & Richard F Schlenk & Martin Schumacher & Lars Bullinger & Harald Binder, 2016. "Identifying Prognostic SNPs in Clinical Cohorts: Complementing Univariate Analyses by Resampling and Multivariable Modeling," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-18, May.
  47. Narajewski, Michał & Ziel, Florian, 2020. "Econometric modelling and forecasting of intraday electricity prices," Journal of Commodity Markets, Elsevier, vol. 19(C).
  48. de Paula, Aureo & Rasul, Imran & Souza, Pedro, 2018. "Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition," CEPR Discussion Papers 12792, C.E.P.R. Discussion Papers.
  49. Donato Ceci & Andrea Silvestrini, 2023. "Nowcasting the state of the Italian economy: The role of financial markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1569-1593, November.
  50. Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1181-1200, September.
  51. Saptarshi Chatterjee & Shrabanti Chowdhury & Sanjib Basu, 2021. "A model‐free approach for testing association," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 511-531, June.
  52. Lubomír Štěpánek & Jana Dlouhá & Patrícia Martinková, 2023. "Item Difficulty Prediction Using Item Text Features: Comparison of Predictive Performance across Machine-Learning Algorithms," Mathematics, MDPI, vol. 11(19), pages 1-30, September.
  53. Cai, Jia & Xiang, Dao-Hong, 2016. "Statistical consistency of coefficient-based conditional quantile regression," Journal of Multivariate Analysis, Elsevier, vol. 149(C), pages 1-12.
  54. Li, Jiahan & Tsiakas, Ilias, 2017. "Equity premium prediction: The role of economic and statistical constraints," Journal of Financial Markets, Elsevier, vol. 36(C), pages 56-75.
  55. António Rua & Carlos Melo Gouveia & Nuno Lourenço, 2020. "Forecasting tourism with targeted predictors in a data-rich environment," Working Papers w202005, Banco de Portugal, Economics and Research Department.
  56. Patricia Rowan & Reena Gupta & Rebecca Lester & Michael Levere & Kristie Liao & Jenna Libersky & Debra Lipson & Andrea Wysocki & Julie Robison & Patricia Bowen, "undated". "A Study of the COVID-19 Outbreak and Response in Connecticut Long-Term Care Facilities: Final Report," Mathematica Policy Research Reports 3b9a215cd22246edbf9abbd41, Mathematica Policy Research.
  57. Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
  58. Suprateek Kundu & David B. Dunson, 2014. "Bayes Variable Selection in Semiparametric Linear Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 437-447, March.
  59. Gregory J. Martin & Ali Yurukoglu, 2017. "Bias in Cable News: Persuasion and Polarization," American Economic Review, American Economic Association, vol. 107(9), pages 2565-2599, September.
  60. Bai, Jushan & Ng, Serena, 2008. "Forecasting economic time series using targeted predictors," Journal of Econometrics, Elsevier, vol. 146(2), pages 304-317, October.
  61. Yue, Lili & Li, Gaorong & Lian, Heng & Wan, Xiang, 2019. "Regression adjustment for treatment effect with multicollinearity in high dimensions," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 17-35.
  62. Fan, Jianqing & Ke, Yuan & Wang, Kaizheng, 2020. "Factor-adjusted regularized model selection," Journal of Econometrics, Elsevier, vol. 216(1), pages 71-85.
  63. Qiu, Yue & Zheng, Yuchen, 2023. "Improving box office projections through sentiment analysis: Insights from regularization-based forecast combinations," Economic Modelling, Elsevier, vol. 125(C).
  64. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure," Journal of Financial Econometrics, Oxford University Press, vol. 21(3), pages 915-958.
  65. Guo, Zhifeng & O'Hanley, Jesse R. & Gibson, Stuart, 2022. "Predicting residential electricity consumption patterns based on smart meter and household data: A case study from the Republic of Ireland," Utilities Policy, Elsevier, vol. 79(C).
  66. Merlijn Breugel & Cancan Qi & Zhongli Xu & Casper-Emil T. Pedersen & Ilya Petoukhov & Judith M. Vonk & Ulrike Gehring & Marijn Berg & Marnix Bügel & Orestes A. Carpaij & Erick Forno & Andréanne Morin , 2022. "Nasal DNA methylation at three CpG sites predicts childhood allergic disease," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
  67. Rana Muhammad Adnan Ikram & Leonardo Goliatt & Ozgur Kisi & Slavisa Trajkovic & Shamsuddin Shahid, 2022. "Covariance Matrix Adaptation Evolution Strategy for Improving Machine Learning Approaches in Streamflow Prediction," Mathematics, MDPI, vol. 10(16), pages 1-30, August.
  68. Patric Müller & Sara Geer, 2015. "The Partial Linear Model in High Dimensions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 580-608, June.
  69. Adam N. Smith & Stephan Seiler & Ishant Aggarwal, 2023. "Optimal Price Targeting," Marketing Science, INFORMS, vol. 42(3), pages 476-499, May.
  70. Mohammad Abdullah & Mohammad Ashraful Ferdous Chowdhury & Ajim Uddin & Syed Moudud‐Ul‐Huq, 2023. "Forecasting nonperforming loans using machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1664-1689, November.
  71. Yi Zhao & Lexin Li & Brian S. Caffo, 2021. "Multimodal neuroimaging data integration and pathway analysis," Biometrics, The International Biometric Society, vol. 77(3), pages 879-889, September.
  72. Cox Lwaka Tamba & Yuan-Li Ni & Yuan-Ming Zhang, 2017. "Iterative sure independence screening EM-Bayesian LASSO algorithm for multi-locus genome-wide association studies," PLOS Computational Biology, Public Library of Science, vol. 13(1), pages 1-20, January.
  73. Nimit Nimana & Narin Petrot, 2019. "Generalized forward–backward splitting with penalization for monotone inclusion problems," Journal of Global Optimization, Springer, vol. 73(4), pages 825-847, April.
  74. Ziel, Florian, 2016. "Iteratively reweighted adaptive lasso for conditional heteroscedastic time series with applications to AR–ARCH type processes," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 773-793.
  75. Yoonsuh Jung, 2018. "Multiple predicting K-fold cross-validation for model selection," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 197-215, January.
  76. Wang, Siyang & Cui, Hengjian, 2015. "A new test for part of high dimensional regression coefficients," Journal of Multivariate Analysis, Elsevier, vol. 137(C), pages 187-203.
  77. Christiansen, Charlotte & Eriksen, Jonas N. & Møller, Stig V., 2019. "Negative house price co-movements and US recessions," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 382-394.
  78. Murat Genç & M. Revan Özkale, 2021. "Usage of the GO estimator in high dimensional linear models," Computational Statistics, Springer, vol. 36(1), pages 217-239, March.
  79. Torossian, Léonard & Picheny, Victor & Faivre, Robert & Garivier, Aurélien, 2020. "A review on quantile regression for stochastic computer experiments," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
  80. Maehashi, Kohei & Shintani, Mototsugu, 2020. "Macroeconomic forecasting using factor models and machine learning: an application to Japan," Journal of the Japanese and International Economies, Elsevier, vol. 58(C).
  81. Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2021. "A machine learning approach to volatility forecasting," CREATES Research Papers 2021-03, Department of Economics and Business Economics, Aarhus University.
  82. repec:dau:papers:123456789/10079 is not listed on IDEAS
  83. Fang, Xiaolei & Paynabar, Kamran & Gebraeel, Nagi, 2017. "Multistream sensor fusion-based prognostics model for systems with single failure modes," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 322-331.
  84. Wang, Qiao & Zhou, Wei & Cheng, Yonggang & Ma, Gang & Chang, Xiaolin & Miao, Yu & Chen, E, 2018. "Regularized moving least-square method and regularized improved interpolating moving least-square method with nonsingular moment matrices," Applied Mathematics and Computation, Elsevier, vol. 325(C), pages 120-145.
  85. Maryam Yashtini, 2021. "Multi-block Nonconvex Nonsmooth Proximal ADMM: Convergence and Rates Under Kurdyka–Łojasiewicz Property," Journal of Optimization Theory and Applications, Springer, vol. 190(3), pages 966-998, September.
  86. Zhang, Ting & Wang, Lei, 2020. "Smoothed empirical likelihood inference and variable selection for quantile regression with nonignorable missing response," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
  87. Timmermann, Allan & Møller, Stig & Pedersen, Thomas & Schütte, Erik Christian Montes, 2021. "Search and Predictability of Prices in the Housing Market," CEPR Discussion Papers 15875, C.E.P.R. Discussion Papers.
  88. Shi, Guiling & Lim, Chae Young & Maiti, Tapabrata, 2019. "Model selection using mass-nonlocal prior," Statistics & Probability Letters, Elsevier, vol. 147(C), pages 36-44.
  89. Olivier Darne & Amelie Charles, 2020. "Nowcasting GDP growth using data reduction methods: Evidence for the French economy," Economics Bulletin, AccessEcon, vol. 40(3), pages 2431-2439.
  90. Yanfang Zhang & Chuanhua Wei & Xiaolin Liu, 2022. "Group Logistic Regression Models with l p,q Regularization," Mathematics, MDPI, vol. 10(13), pages 1-15, June.
  91. Plakandaras, Vasilios & Gupta, Rangan & Gogas, Periklis & Papadimitriou, Theophilos, 2015. "Forecasting the U.S. real house price index," Economic Modelling, Elsevier, vol. 45(C), pages 259-267.
  92. Anastasis Kratsios & Cody B. Hyndman, 2017. "Non-Euclidean Conditional Expectation and Filtering," Papers 1710.05829, arXiv.org, revised Sep 2018.
  93. Sijian Wang & Bin Nan & Ji Zhu & David G. Beer, 2008. "Doubly Penalized Buckley–James Method for Survival Data with High-Dimensional Covariates," Biometrics, The International Biometric Society, vol. 64(1), pages 132-140, March.
  94. Xiang-Jie Li & Xue-Jun Ma & Jing-Xiao Zhang, 2017. "Robust feature screening for varying coefficient models via quantile partial correlation," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(1), pages 17-49, January.
  95. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Estimating global bank network connectedness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 1-15, January.
  96. Wang, Tao & Zhu, Lixing, 2013. "Sparse sufficient dimension reduction using optimal scoring," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 223-232.
  97. Marius Clemens & Konstantin A. Kholodilin & Claus Michelsen, 2020. "Fortschreibung der Kapazitätsauslastung in der TFP-Berechnung: Endbericht; Kurzexpertise im Auftrag des Bundesfinanzministeriums (fe 3/19)," DIW Berlin: Politikberatung kompakt, DIW Berlin, German Institute for Economic Research, volume 127, number pbk160, Enero-Abr.
  98. Ciaran O'Connor & Joseph Collins & Steven Prestwich & Andrea Visentin, 2024. "Electricity Price Forecasting in the Irish Balancing Market," Papers 2402.06714, arXiv.org.
  99. Sebri, Maamar & Dachraoui, Hajer, 2021. "Natural resources and income inequality: A meta-analytic review," Resources Policy, Elsevier, vol. 74(C).
  100. Lee, Juyong & Reiner, David M., 2023. "Determinants of public preferences on low-carbon energy sources: Evidence from the United Kingdom," Energy, Elsevier, vol. 284(C).
  101. Janusz Sowinski, 2021. "The Impact of the Selection of Exogenous Variables in the ANFIS Model on the Results of the Daily Load Forecast in the Power Company," Energies, MDPI, vol. 14(2), pages 1-18, January.
  102. Ard Reijer, 2013. "Forecasting Dutch GDP and inflation using alternative factor model specifications based on large and small datasets," Empirical Economics, Springer, vol. 44(2), pages 435-453, April.
  103. Menon, Aditya Krishna & Cai, Chen & Wang, Weihong & Wen, Tao & Chen, Fang, 2015. "Fine-grained OD estimation with automated zoning and sparsity regularisation," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 150-172.
  104. Dmitriy Drusvyatskiy & Adrian S. Lewis, 2018. "Error Bounds, Quadratic Growth, and Linear Convergence of Proximal Methods," Mathematics of Operations Research, INFORMS, vol. 43(3), pages 919-948, August.
  105. Huei-Wen Teng & Yu-Hsien Li, 2023. "Can deep neural networks outperform Fama-MacBeth regression and other supervised learning approaches in stock returns prediction with asset-pricing factors?," Digital Finance, Springer, vol. 5(1), pages 149-182, March.
  106. Valencia, Oscar & Parra, Diego A. & Díaz, Juan Camilo, 2022. "Assessing Macro-Fiscal Risk for Latin American and Caribbean Countries," IDB Publications (Working Papers) 12482, Inter-American Development Bank.
  107. VÁZQUEZ-ALCOCER, Alan & SCHOEN, Eric D. & GOOS, Peter, 2018. "A mixed integer optimization approach for model selection in screening experiments," Working Papers 2018007, University of Antwerp, Faculty of Business and Economics.
  108. Yu-Zhu Tian & Man-Lai Tang & Wai-Sum Chan & Mao-Zai Tian, 2021. "Bayesian bridge-randomized penalized quantile regression for ordinal longitudinal data, with application to firm’s bond ratings," Computational Statistics, Springer, vol. 36(2), pages 1289-1319, June.
  109. Shannon M Lynch & Elizabeth Handorf & Kristen A Sorice & Elizabeth Blackman & Lisa Bealin & Veda N Giri & Elias Obeid & Camille Ragin & Mary Daly, 2020. "The effect of neighborhood social environment on prostate cancer development in black and white men at high risk for prostate cancer," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-18, August.
  110. Satre-Meloy, Aven, 2019. "Investigating structural and occupant drivers of annual residential electricity consumption using regularization in regression models," Energy, Elsevier, vol. 174(C), pages 148-168.
  111. Seokho Moon & Hansam Cho & Eunji Koh & Yong Sung Cho & Hyoung Lok Oh & Younghoon Kim & Seoung Bum Kim, 2022. "Remanufacturing Decision-Making for Gas Insulated Switchgear with Remaining Useful Life Prediction," Sustainability, MDPI, vol. 14(19), pages 1-13, September.
  112. Mkhadri, Abdallah & Ouhourane, Mohamed, 2013. "An extended variable inclusion and shrinkage algorithm for correlated variables," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 631-644.
  113. Paul Harris & Bruno Lanfranco & Binbin Lu & Alexis Comber, 2020. "Influence of Geographical Effects in Hedonic Pricing Models for Grass-Fed Cattle in Uruguay," Agriculture, MDPI, vol. 10(7), pages 1-17, July.
  114. Dengluan Dai & Anmin Tang & Jinli Ye, 2023. "High-Dimensional Variable Selection for Quantile Regression Based on Variational Bayesian Method," Mathematics, MDPI, vol. 11(10), pages 1-22, May.
  115. Anda Tang & Pei Quan & Lingfeng Niu & Yong Shi, 2022. "A Survey for Sparse Regularization Based Compression Methods," Annals of Data Science, Springer, vol. 9(4), pages 695-722, August.
  116. Colombo, Emilio & Pelagatti, Matteo, 2020. "Statistical learning and exchange rate forecasting," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1260-1289.
  117. Edward I. Altman & Marco Balzano & Alessandro Giannozzi & Stjepan Srhoj, 2023. "Revisiting SME default predictors: The Omega Score," Journal of Small Business Management, Taylor & Francis Journals, vol. 61(6), pages 2383-2417, November.
  118. Shen, Meng & Lu, Yujie & Wei, Kua Harn & Cui, Qingbin, 2020. "Prediction of household electricity consumption and effectiveness of concerted intervention strategies based on occupant behaviour and personality traits," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
  119. Hyonho Chun & Sündüz Keleş, 2010. "Sparse partial least squares regression for simultaneous dimension reduction and variable selection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(1), pages 3-25, January.
  120. Gary Koop & Dimitris Korobilis, 2023. "Bayesian Dynamic Variable Selection In High Dimensions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 1047-1074, August.
  121. Pavel Atanasov & Phillip Rescober & Eric Stone & Samuel A. Swift & Emile Servan-Schreiber & Philip Tetlock & Lyle Ungar & Barbara Mellers, 2017. "Distilling the Wisdom of Crowds: Prediction Markets vs. Prediction Polls," Management Science, INFORMS, vol. 63(3), pages 691-706, March.
  122. Matthias Weber & Martin Schumacher & Harald Binder, 2014. "Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs," Tinbergen Institute Discussion Papers 14-089/I, Tinbergen Institute.
  123. Bruce E. Hansen, 2016. "The Risk of James--Stein and Lasso Shrinkage," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1456-1470, December.
  124. Daniel Borup & Erik Christian Montes Schütte, 2019. "In search of a job: Forecasting employment growth using Google Trends," CREATES Research Papers 2019-13, Department of Economics and Business Economics, Aarhus University.
  125. Daniel Borup & Philippe Goulet Coulombe & Erik Christian Montes Schütte & David E. Rapach & Sander Schwenk-Nebbe, 2022. "The Anatomy of Out-of-Sample Forecasting Accuracy," FRB Atlanta Working Paper 2022-16, Federal Reserve Bank of Atlanta.
  126. Milan Fičura, 2019. "Forecasting Cross-Section of Stock Returns with Realised Moments," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2019(2), pages 71-84.
  127. Raquel Nadal Cesar Gonçalves, 2022. "Nowcasting Brazilian GDP with Electronic Payments Data," Working Papers Series 564, Central Bank of Brazil, Research Department.
  128. Lucian Belascu & Alexandra Horobet & Georgiana Vrinceanu & Consuela Popescu, 2021. "Performance Dissimilarities in European Union Manufacturing: The Effect of Ownership and Technological Intensity," Sustainability, MDPI, vol. 13(18), pages 1-19, September.
  129. Athey, Susan & Imbens, Guido W., 2019. "Machine Learning Methods Economists Should Know About," Research Papers 3776, Stanford University, Graduate School of Business.
  130. Zachary Garfield & Ryan Schacht & Emily Post & Dominique Ingram & Andrea Uehling & Shane Macfarlan, 2021. "The content and structure of reputation domains across human societies: a view from the evolutionary social sciences," Post-Print hal-03368986, HAL.
  131. Candelon, B. & Hurlin, C. & Tokpavi, S., 2012. "Sampling error and double shrinkage estimation of minimum variance portfolios," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 511-527.
  132. Waleed DHHAN & Sohel RANA & TahaALSHAYBAWEE & Habshah MIDI, 2017. "Elastic Net for Single Index Support Vector Regression Model," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(2), pages 195-210.
  133. Bostanci, Gorkem & Yilmaz, Kamil, 2020. "How connected is the global sovereign credit risk network?," Journal of Banking & Finance, Elsevier, vol. 113(C).
  134. Ardyn Nordstrom, 2021. "Can Interventions Targeting Community Attitudes Improve Education for Marginalized Students? Evidence from a Mixed-Methods Experimental Design in Zimbabwe," Working Paper 1472, Economics Department, Queen's University.
  135. Hoonseong Oh & Sangmin Lee, 2021. "Evaluation and Interpretation of Tourist Satisfaction for Local Korean Festivals Using Explainable AI," Sustainability, MDPI, vol. 13(19), pages 1-18, September.
  136. Xianyi Wu & Xian Zhou, 2019. "On Hodges’ superefficiency and merits of oracle property in model selection," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(5), pages 1093-1119, October.
  137. Onur Şeref & Wanpracha Chaovalitwongse & J. Brooks, 2014. "Relaxing support vectors for classification," Annals of Operations Research, Springer, vol. 216(1), pages 229-255, May.
  138. Mingrui Zhong & Zanhua Yin & Zhichao Wang, 2023. "Variable Selection for Sparse Logistic Regression with Grouped Variables," Mathematics, MDPI, vol. 11(24), pages 1-21, December.
  139. Ballering, Aranka V. & Bonvanie, Irma J. & Olde Hartman, Tim C. & Monden, Rei & Rosmalen, Judith G.M., 2020. "Gender and sex independently associate with common somatic symptoms and lifetime prevalence of chronic disease," Social Science & Medicine, Elsevier, vol. 253(C).
  140. Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021. "Nowcasting GDP using machine-learning algorithms: A real-time assessment," International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
  141. Scutari Marco & Balding David & Mackay Ian, 2013. "Improving the efficiency of genomic selection," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(4), pages 517-527, August.
  142. Mr. Jorge A Chan-Lau, 2017. "Variance Decomposition Networks: Potential Pitfalls and a Simple Solution," IMF Working Papers 2017/107, International Monetary Fund.
  143. Ascarza, & Neslin, & Netzer, & Lemmens, Aurélie & Anderson, Zachery & Fader, Peter S. & Gupta, S. & Hardie, B.G.S. & Libai, Barak & Neal, David & Provost, Foster, 2018. "In pursuit of enhanced customer retention management : Review, key issues, and future directions," Other publications TiSEM 28a90d28-6daf-42f1-bd8e-e, Tilburg University, School of Economics and Management.
  144. Ismail Shah & Hina Naz & Sajid Ali & Amani Almohaimeed & Showkat Ahmad Lone, 2023. "A New Quantile-Based Approach for LASSO Estimation," Mathematics, MDPI, vol. 11(6), pages 1-13, March.
  145. Li-Pang Chen, 2021. "Feature screening based on distance correlation for ultrahigh-dimensional censored data with covariate measurement error," Computational Statistics, Springer, vol. 36(2), pages 857-884, June.
  146. Qin, Yichen & Wang, Linna & Li, Yang & Li, Rong, 2023. "Visualization and assessment of model selection uncertainty," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
  147. Kimia Keshanian & Daniel Zantedeschi & Kaushik Dutta, 2022. "Features Selection as a Nash-Bargaining Solution: Applications in Online Advertising and Information Systems," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2485-2501, September.
  148. Susan Athey & Guido W. Imbens & Stefan Wager, 2018. "Approximate residual balancing: debiased inference of average treatment effects in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 597-623, September.
  149. Mihee Lee & Haipeng Shen & Jianhua Z. Huang & J. S. Marron, 2010. "Biclustering via Sparse Singular Value Decomposition," Biometrics, The International Biometric Society, vol. 66(4), pages 1087-1095, December.
  150. Lee, Ji Hyung & Shi, Zhentao & Gao, Zhan, 2022. "On LASSO for predictive regression," Journal of Econometrics, Elsevier, vol. 229(2), pages 322-349.
  151. Dumitrescu, Elena & Hué, Sullivan & Hurlin, Christophe & Tokpavi, Sessi, 2022. "Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1178-1192.
  152. Li Yun & O’Connor George T. & Dupuis Josée & Kolaczyk Eric, 2015. "Modeling gene-covariate interactions in sparse regression with group structure for genome-wide association studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(3), pages 265-277, June.
  153. Lago, Jesus & Marcjasz, Grzegorz & De Schutter, Bart & Weron, Rafał, 2021. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Applied Energy, Elsevier, vol. 293(C).
  154. Julien Chevallier & Dominique Guégan & Stéphane Goutte, 2021. "Is It Possible to Forecast the Price of Bitcoin?," Forecasting, MDPI, vol. 3(2), pages 1-44, May.
  155. Diego Vidaurre & Concha Bielza & Pedro Larrañaga, 2013. "A Survey of L1 Regression," International Statistical Review, International Statistical Institute, vol. 81(3), pages 361-387, December.
  156. Heiss, Florian & Hetzenecker, Stephan & Osterhaus, Maximilian, 2019. "Nonparametric estimation of the random coefficients model: An elastic net approach," DICE Discussion Papers 326, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
  157. Caterina Schiavoni & Franz Palm & Stephan Smeekes & Jan van den Brakel, 2021. "A dynamic factor model approach to incorporate Big Data in state space models for official statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 324-353, January.
  158. Brent Johnson & Limin Peng, 2008. "Rank-based variable selection," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(3), pages 241-252.
  159. Hoxha, Julian & Çodur, Muhammed Yasin & Mustafaraj, Enea & Kanj, Hassan & El Masri, Ali, 2023. "Prediction of transportation energy demand in Türkiye using stacking ensemble models: Methodology and comparative analysis," Applied Energy, Elsevier, vol. 350(C).
  160. Daye, Z. John & Jeng, X. Jessie, 2009. "Shrinkage and model selection with correlated variables via weighted fusion," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1284-1298, February.
  161. Leandro da Silva Pereira & Lucas Monteiro Chaves & Devanil Jaques de Souza, 2017. "An Intuitive Geometric Approach to the Gauss Markov Theorem," The American Statistician, Taylor & Francis Journals, vol. 71(1), pages 67-70, January.
  162. Luiz Renato Lima & Lucas Lúcio Godeiro, 2023. "Equity‐premium prediction: Attention is all you need," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 105-122, January.
  163. T. Cai & J. Huang & L. Tian, 2009. "Regularized Estimation for the Accelerated Failure Time Model," Biometrics, The International Biometric Society, vol. 65(2), pages 394-404, June.
  164. Mehmet Caner & Xu Han & Yoonseok Lee, 2018. "Adaptive Elastic Net GMM Estimation With Many Invalid Moment Conditions: Simultaneous Model and Moment Selection," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 24-46, January.
  165. Luis Fernando Melo-Velandia & Juan J. Ospina-Tejeiro & Julian A. Parra-Polania, 2020. "Effects of Banco de la Republica’s Communication on the Yield Curve," Borradores de Economia 1137, Banco de la Republica de Colombia.
  166. Belli, Edoardo, 2022. "Smoothly adaptively centered ridge estimator," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
  167. Lima, Luiz Renato & Meng, Fanning & Godeiro, Lucas, 2020. "Quantile forecasting with mixed-frequency data," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1149-1162.
  168. Zhihua Sun & Yi Liu & Kani Chen & Gang Li, 2022. "Broken adaptive ridge regression for right-censored survival data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(1), pages 69-91, February.
  169. International Monetary Fund, 2017. "Japan: Financial Sector Assessment Program-Technical Note-Systemic Risk Analysis and Stress Testing the Financial Sector," IMF Staff Country Reports 2017/285, International Monetary Fund.
  170. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Specification Choices in Quantile Regression for Empirical Macroeconomics," Working Papers 22-25, Federal Reserve Bank of Cleveland.
  171. Hu, Qinqin & Zeng, Peng & Lin, Lu, 2015. "The dual and degrees of freedom of linearly constrained generalized lasso," Computational Statistics & Data Analysis, Elsevier, vol. 86(C), pages 13-26.
  172. Siliang Zhang & Yunxiao Chen, 2022. "Computation for Latent Variable Model Estimation: A Unified Stochastic Proximal Framework," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1473-1502, December.
  173. Tomay Solomon & Behzad Esmaeili, 2021. "Examining the Relationship between Mindfulness, Personality, and National Culture for Construction Safety," IJERPH, MDPI, vol. 18(9), pages 1-21, May.
  174. Soyeon Kim & Veerabhadran Baladandayuthapani & J. Jack Lee, 2017. "Prediction-Oriented Marker Selection (PROMISE): With Application to High-Dimensional Regression," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 217-245, June.
  175. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2021. "Point and density forecasting of macroeconomic and financial uncertainties of the USA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 700-707, July.
  176. Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
  177. Pierre L. Siklos & Martin Stefan & Claudia Wellenreuther, 2020. "Metal prices made in China? A network analysis of industrial metal futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(9), pages 1354-1374, September.
  178. Guillermo A Cecchi & Lejian Huang & Javeria Ali Hashmi & Marwan Baliki & María V Centeno & Irina Rish & A Vania Apkarian, 2012. "Predictive Dynamics of Human Pain Perception," PLOS Computational Biology, Public Library of Science, vol. 8(10), pages 1-12, October.
  179. Wong William W.L. & Griesman Josh & Feng Zeny Z., 2014. "Imputing genotypes using regularized generalized linear regression models," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(5), pages 1-11, October.
  180. Jinzhou Li & Marloes H. Maathuis, 2021. "GGM knockoff filter: False discovery rate control for Gaussian graphical models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(3), pages 534-558, July.
  181. Barbara Rossi, 2019. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," Working Papers 1162, Barcelona School of Economics.
  182. Hanwen Huang, 2017. "Controlling the false discoveries in LASSO," Biometrics, The International Biometric Society, vol. 73(4), pages 1102-1110, December.
  183. Xue Gong & Weiguo Zhang & Yuan Zhao & Xin Ye, 2023. "Forecasting stock volatility with a large set of predictors: A new forecast combination method," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1622-1647, November.
  184. Aaron Chalfin & Benjamin Hansen & Jason Lerner & Lucie Parker, 2019. "Reducing Crime Through Environmental Design: Evidence from a Randomized Experiment of Street Lighting in New York City," NBER Working Papers 25798, National Bureau of Economic Research, Inc.
  185. Guan Yu & Yufeng Liu, 2016. "Sparse Regression Incorporating Graphical Structure Among Predictors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 707-720, April.
  186. Lin, Huazhen & Peng, Heng, 2013. "Smoothed rank correlation of the linear transformation regression model," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 615-630.
  187. Xia Zheng & Yaohua Rong & Ling Liu & Weihu Cheng, 2021. "A More Accurate Estimation of Semiparametric Logistic Regression," Mathematics, MDPI, vol. 9(19), pages 1-12, September.
  188. Roberto Marfè & Julien Pénasse, 2020. "Measuring Macroeconomic Tail Risk," Carlo Alberto Notebooks 621, Collegio Carlo Alberto.
  189. Raphaël Douady & Yao Kuang, 2020. "Crisis Risk Prediction with Concavity from Polymodel," Working Papers hal-03018481, HAL.
  190. Luiz Renato Lima & Lucas Lúcio Godeiro & Mohammed Mohsin, 2021. "Time-Varying Dictionary and the Predictive Power of FED Minutes," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 149-181, January.
  191. David A. Mascio & Marat Molyboga & Frank J. Fabozzi, 2023. "The battle of the factors: Macroeconomic variables or investor sentiment?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2280-2291, December.
  192. Ardia, David & Bluteau, Keven & Kassem, Alaa, 2021. "A century of Economic Policy Uncertainty through the French–Canadian lens," Economics Letters, Elsevier, vol. 205(C).
  193. Shen, Haipeng & Huang, Jianhua Z., 2008. "Sparse principal component analysis via regularized low rank matrix approximation," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1015-1034, July.
  194. Yen-Shiu Chin & Ting-Li Chen, 2016. "Minimizing variable selection criteria by Markov chain Monte Carlo," Computational Statistics, Springer, vol. 31(4), pages 1263-1286, December.
  195. Baaken, Dominik & Hess, Sebastian, 2021. "Regionale Milchmengenprognose: Regressionsmodelle und Maschinelles Lernen im Vergleich," 61st Annual Conference, Berlin, Germany, September 22-24, 2021 317056, German Association of Agricultural Economists (GEWISOLA).
  196. Shi, Minghui & Dunson, David B., 2011. "Bayesian variable selection via particle stochastic search," Statistics & Probability Letters, Elsevier, vol. 81(2), pages 283-291, February.
  197. Nicolai Meinshausen & Peter Bühlmann, 2010. "Stability selection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(4), pages 417-473, September.
  198. Caiya Zhang & Yanbiao Xiang, 2016. "On the oracle property of adaptive group Lasso in high-dimensional linear models," Statistical Papers, Springer, vol. 57(1), pages 249-265, March.
  199. Ying Sheng & Yifei Sun & Chiung‐Yu Huang & Mi‐Ok Kim, 2022. "Synthesizing external aggregated information in the presence of population heterogeneity: A penalized empirical likelihood approach," Biometrics, The International Biometric Society, vol. 78(2), pages 679-690, June.
  200. Mitzi Isabel Cubilla‐Montilla & Purificación Galindo‐Villardón & Ana Belén Nieto‐Librero & María Purificación Vicente Galindo & Isabel María García‐Sánchez, 2020. "What companies do not disclose about their environmental policy and what institutional pressures may do to respect," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 27(3), pages 1181-1197, May.
  201. Ian W. McKeague & Min Qian, 2015. "An Adaptive Resampling Test for Detecting the Presence of Significant Predictors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1422-1433, December.
  202. Pierre Alquier & Karim Lounici, 2010. "Pac-Bayesian Bounds for Sparse Regression Estimation with Exponential Weights," Working Papers 2010-40, Center for Research in Economics and Statistics.
  203. Alexis Comber & Paul Harris, 2018. "Geographically weighted elastic net logistic regression," Journal of Geographical Systems, Springer, vol. 20(4), pages 317-341, October.
  204. Bantis, Evripidis & Clements, Michael P. & Urquhart, Andrew, 2023. "Forecasting GDP growth rates in the United States and Brazil using Google Trends," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1909-1924.
  205. Korzeń, M. & Jaroszewicz, S. & Klęsk, P., 2013. "Logistic regression with weight grouping priors," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 281-298.
  206. Victor DeMiguel & Javier Gil-Bazo & Francisco J. Nogales & André A. P. Santos, 2021. "Can Machine Learning Help to Select Portfolios of Mutual Funds?," Working Papers 1245, Barcelona School of Economics.
  207. Weibing Li & Thierry Chekouo, 2022. "Bayesian group selection with non-local priors," Computational Statistics, Springer, vol. 37(1), pages 287-302, March.
  208. Mielniczuk, Jan & Teisseyre, Paweł, 2014. "Using random subspace method for prediction and variable importance assessment in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 725-742.
  209. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
  210. Thomas Kneib & Torsten Hothorn & Gerhard Tutz, 2009. "Variable Selection and Model Choice in Geoadditive Regression Models," Biometrics, The International Biometric Society, vol. 65(2), pages 626-634, June.
  211. Lee, Kyu Ha & Chakraborty, Sounak & Sun, Jianguo, 2017. "Variable selection for high-dimensional genomic data with censored outcomes using group lasso prior," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 1-13.
  212. Harold A. Hernández-Roig & M. Carmen Aguilera-Morillo & Rosa E. Lillo, 2021. "Functional Modeling of High-Dimensional Data: A Manifold Learning Approach," Mathematics, MDPI, vol. 9(4), pages 1-22, February.
  213. Adam D. Nowak & Bradley S. Price & Patrick S. Smith, 2021. "Real Estate Dictionaries Across Space and Time," The Journal of Real Estate Finance and Economics, Springer, vol. 62(1), pages 139-163, January.
  214. Seungyeul Yoo & Abhilasha Sinha & Dawei Yang & Nasser K. Altorki & Radhika Tandon & Wenhui Wang & Deebly Chavez & Eunjee Lee & Ayushi S. Patel & Takashi Sato & Ranran Kong & Bisen Ding & Eric E. Schad, 2022. "Integrative network analysis of early-stage lung adenocarcinoma identifies aurora kinase inhibition as interceptor of invasion and progression," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
  215. Zaremba, Adam & Kizys, Renatas & Tzouvanas, Panagiotis & Aharon, David Y. & Demir, Ender, 2021. "The quest for multidimensional financial immunity to the COVID-19 pandemic: Evidence from international stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
  216. Sheng, Ying & Wang, Qihua, 2019. "Simultaneous variable selection and class fusion with penalized distance criterion based classifiers," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 138-152.
  217. Feihan Lu & Yao Zheng & Harrington Cleveland & Chris Burton & David Madigan, 2018. "Bayesian hierarchical vector autoregressive models for patient-level predictive modeling," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-27, December.
  218. Li, Qing & Yu, Shuai & Échevin, Damien & Fan, Min, 2022. "Is poverty predictable with machine learning? A study of DHS data from Kyrgyzstan," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
  219. Simona Buscemi & Antonella Plaia, 2020. "Model selection in linear mixed-effect models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(4), pages 529-575, December.
  220. Rao, Akhil & Burgess, Matthew & Kaffine, Daniel, 2020. "Orbital-use fees could more than quadruple the value of the space industry," MPRA Paper 112708, University Library of Munich, Germany.
  221. de Souza, Erick Almeida & Silva, Stéphanie Andrade & Vieira, Bruno Hebling & Salmon, Carlos Ernesto Garrido, 2023. "fMRI functional connectivity is a better predictor of general intelligence than cortical morphometric features and ICA parcellation order affects predictive performance," Intelligence, Elsevier, vol. 97(C).
  222. Giorgos Stathopoulos & Colin N. Jones, 2019. "An Inertial Parallel and Asynchronous Forward–Backward Iteration for Distributed Convex Optimization," Journal of Optimization Theory and Applications, Springer, vol. 182(3), pages 1088-1119, September.
  223. John M. Abowd & Joelle Hillary Abramowitz & Margaret Catherine Levenstein & Kristin McCue & Dhiren Patki & Trivellore Raghunathan & Ann Michelle Rodgers & Matthew D. Shapiro & Nada Wasi & Dawn Zinsser, 2021. "Finding Needles in Haystacks: Multiple-Imputation Record Linkage Using Machine Learning," Working Papers 22-11, Federal Reserve Bank of Boston.
  224. Posch, Konstantin & Arbeiter, Maximilian & Pilz, Juergen, 2020. "A novel Bayesian approach for variable selection in linear regression models," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
  225. Gerda Claeskens, 2012. "Focused estimation and model averaging with penalization methods: an overview," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(3), pages 272-287, August.
  226. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
  227. Ming Yi & Ruoqing Zhu & Robert M Stephens, 2018. "GradientScanSurv—An exhaustive association test method for gene expression data with censored survival outcome," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-28, December.
  228. Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2022. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from The Lasso Regularization and Inferential Techniques," Working Papers of the African Governance and Development Institute. 22/061, African Governance and Development Institute..
  229. Junyang Qian & Yosuke Tanigawa & Wenfei Du & Matthew Aguirre & Chris Chang & Robert Tibshirani & Manuel A Rivas & Trevor Hastie, 2020. "A fast and scalable framework for large-scale and ultrahigh-dimensional sparse regression with application to the UK Biobank," PLOS Genetics, Public Library of Science, vol. 16(10), pages 1-30, October.
  230. Dominique Guegan & Bertrand Hassani, 2017. "Regulatory Learning: how to supervise machine learning models? An application to credit scoring," Documents de travail du Centre d'Economie de la Sorbonne 17034r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Sep 2017.
  231. Takashi Nakazawa, 2022. "Constructing GDP Nowcasting Models Using Alternative Data," Bank of Japan Working Paper Series 22-E-9, Bank of Japan.
  232. Mao Takongmo, Charles-O. & Touré, Adam, 2023. "Trade openness and connectedness of national productions: Do financial openness, economic specialization, and the size of the country matter?," Economic Modelling, Elsevier, vol. 125(C).
  233. Siwei Xia & Yuehan Yang & Hu Yang, 2022. "Sparse Laplacian Shrinkage with the Graphical Lasso Estimator for Regression Problems," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 255-277, March.
  234. Ueki, Masao & Kawasaki, Yoshinori, 2013. "Multiple choice from competing regression models under multicollinearity based on standardized update," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 31-41.
  235. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
  236. Zuber Verena & Strimmer Korbinian, 2011. "High-Dimensional Regression and Variable Selection Using CAR Scores," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-27, July.
  237. Huazhen Lin & Hyokyoung G. Hong & Baoying Yang & Wei Liu & Yong Zhang & Gang-Zhi Fan & Yi Li, 2019. "Nonparametric Time-Varying Coefficient Models for Panel Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(3), pages 548-566, December.
  238. Yong Zhang & Wanzhou Ye & Jianjun Zhang, 2017. "A generalized elastic net regularization with smoothed $$\ell _{q}$$ ℓ q penalty for sparse vector recovery," Computational Optimization and Applications, Springer, vol. 68(2), pages 437-454, November.
  239. Patric Müller & Sara Geer, 2016. "Censored linear model in high dimensions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 75-92, March.
  240. Shuichi Kawano, 2014. "Selection of tuning parameters in bridge regression models via Bayesian information criterion," Statistical Papers, Springer, vol. 55(4), pages 1207-1223, November.
  241. Joscha Krause & Jan Pablo Burgard & Domingo Morales, 2022. "Robust prediction of domain compositions from uncertain data using isometric logratio transformations in a penalized multivariate Fay–Herriot model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 76(1), pages 65-96, February.
  242. Lihua Cai & Honglong Wu & Dongfang Li & Ke Zhou & Fuhao Zou, 2015. "Type 2 Diabetes Biomarkers of Human Gut Microbiota Selected via Iterative Sure Independent Screening Method," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-15, October.
  243. Yize Zhao & Matthias Chung & Brent A. Johnson & Carlos S. Moreno & Qi Long, 2016. "Hierarchical Feature Selection Incorporating Known and Novel Biological Information: Identifying Genomic Features Related to Prostate Cancer Recurrence," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1427-1439, October.
  244. Jayesh Thaker & Robert Höller, 2022. "A Comparative Study of Time Series Forecasting of Solar Energy Based on Irradiance Classification," Energies, MDPI, vol. 15(8), pages 1-26, April.
  245. Ulrike Schneider & Martin Wagner, 2012. "Catching Growth Determinants with the Adaptive Lasso," German Economic Review, Verein für Socialpolitik, vol. 13(1), pages 71-85, February.
  246. Fabio Caccioli & Imre Kondor & Matteo Marsili & Susanne Still, 2014. "$L_p$ regularized portfolio optimization," Papers 1404.4040, arXiv.org.
  247. Krüger, Jens J. & Rhiel, Mathias, 2016. "Determinants of ICT infrastructure: A cross-country statistical analysis," Darmstadt Discussion Papers in Economics 228, Darmstadt University of Technology, Department of Law and Economics.
  248. Jin, Xiaoyu & Xiao, Fu & Zhang, Chong & Chen, Zhijie, 2022. "Semi-supervised learning based framework for urban level building electricity consumption prediction," Applied Energy, Elsevier, vol. 328(C).
  249. Rosember Guerra-Urzola & Niek C. Schipper & Anya Tonne & Klaas Sijtsma & Juan C. Vera & Katrijn Deun, 2023. "Sparsifying the least-squares approach to PCA: comparison of lasso and cardinality constraint," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(1), pages 269-286, March.
  250. Lycheva, Maria & Mironenkov, Alexey & Kurbatskii, Alexey & Fantazzini, Dean, 2022. "Forecasting oil prices with penalized regressions, variance risk premia and Google data," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 28-49.
  251. Rohart, Florian & San Cristobal, Magali & Laurent, Béatrice, 2014. "Selection of fixed effects in high dimensional linear mixed models using a multicycle ECM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 209-222.
  252. Borup, Daniel & Christensen, Bent Jesper & Mühlbach, Nicolaj Søndergaard & Nielsen, Mikkel Slot, 2023. "Targeting predictors in random forest regression," International Journal of Forecasting, Elsevier, vol. 39(2), pages 841-868.
  253. Billio, Monica & Casarin, Roberto & Rossini, Luca, 2019. "Bayesian nonparametric sparse VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 97-115.
  254. Gabauer, David & Gupta, Rangan & Marfatia, Hardik A. & Miller, Stephen M., 2024. "Estimating U.S. housing price network connectedness: Evidence from dynamic Elastic Net, Lasso, and ridge vector autoregressive models," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 349-362.
  255. Diebold, Francis X. & Shin, Minchul, 2019. "Machine learning for regularized survey forecast combination: Partially-egalitarian LASSO and its derivatives," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1679-1691.
  256. Chen, Jian & Katchova, Ani L. & Zhou, Chenxi, 2021. "Agricultural loan delinquency prediction using machine learning methods," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 24(5), May.
  257. Enrico Bergamini & Georg Zachmann, 2020. "Exploring EU’s Regional Potential in Low-Carbon Technologies," Sustainability, MDPI, vol. 13(1), pages 1-28, December.
  258. Fang, Tong & Lee, Tae-Hwy & Su, Zhi, 2020. "Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 36-49.
  259. Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big data analytics: a new perspective," Globalization Institute Working Papers 268, Federal Reserve Bank of Dallas.
  260. Doron Avramov & Guy Kaplanski & Avanidhar Subrahmanyam, 2022. "Postfundamentals Price Drift in Capital Markets: A Regression Regularization Perspective," Management Science, INFORMS, vol. 68(10), pages 7658-7681, October.
  261. David Kaplan, 2021. "On the Quantification of Model Uncertainty: A Bayesian Perspective," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 215-238, March.
  262. Amanda Fitzgerald & Naoise Mac Giollabhui & Louise Dolphin & Robert Whelan & Barbara Dooley, 2018. "Dissociable psychosocial profiles of adolescent substance users," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-16, August.
  263. Lu Yang & Lei Yang & Xue Cui, 2023. "Sovereign default network and currency risk premia," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-22, December.
  264. repec:ipg:wpaper:2014-473 is not listed on IDEAS
  265. Zhang, Yaojie & Wang, Yudong, 2023. "Forecasting crude oil futures market returns: A principal component analysis combination approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 659-673.
  266. Sophie Brana & Dalila Chenaf-Nicet & Delphine Lahet, 2023. "Drivers of cross-border bank claims: The role of foreign-owned banks in emerging countries," Working Papers 2023.06, International Network for Economic Research - INFER.
  267. Bennet Gebken & Katharina Bieker & Sebastian Peitz, 2023. "On the structure of regularization paths for piecewise differentiable regularization terms," Journal of Global Optimization, Springer, vol. 85(3), pages 709-741, March.
  268. Artem Sokolov & Daniel E Carlin & Evan O Paull & Robert Baertsch & Joshua M Stuart, 2016. "Pathway-Based Genomics Prediction using Generalized Elastic Net," PLOS Computational Biology, Public Library of Science, vol. 12(3), pages 1-23, March.
  269. Haixiang Zhang & Jun Chen & Zhigang Li & Lei Liu, 2021. "Testing for Mediation Effect with Application to Human Microbiome Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(2), pages 313-328, July.
  270. Manisha Sanjay Sirsat & Paula Rodrigues Oblessuc & Ricardo S. Ramiro, 2022. "Genomic Prediction of Wheat Grain Yield Using Machine Learning," Agriculture, MDPI, vol. 12(9), pages 1-12, September.
  271. Carroll Paula & Murphy Tadhg & Hanley Michael & Dempsey Daniel & Dunne John, 2018. "Household Classification Using Smart Meter Data," Journal of Official Statistics, Sciendo, vol. 34(1), pages 1-25, March.
  272. Amélie Charles & Olivier Darné, 2022. "Backcasting world trade growth using data reduction methods," The World Economy, Wiley Blackwell, vol. 45(10), pages 3169-3191, October.
  273. Alena Skolkova, 2023. "Instrumental Variable Estimation with Many Instruments Using Elastic-Net IV," CERGE-EI Working Papers wp759, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
  274. Kubus Mariusz, 2020. "Evaluation of Resampling Methods in the Class Unbalance Problem," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 24(1), pages 39-50, March.
  275. Roberto S. Mariano & Suleyman Ozmucur, 2021. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 383-400, December.
  276. Thitiphat Klinsuwan & Wachiraphong Ratiphaphongthon & Rabian Wangkeeree & Rattanaporn Wangkeeree & Chatchai Sirisamphanwong, 2023. "Evaluation of Machine Learning Algorithms for Supervised Anomaly Detection and Comparison between Static and Dynamic Thresholds in Photovoltaic Systems," Energies, MDPI, vol. 16(4), pages 1-22, February.
  277. Ning Li & Hu Yang, 2021. "Nonnegative estimation and variable selection under minimax concave penalty for sparse high-dimensional linear regression models," Statistical Papers, Springer, vol. 62(2), pages 661-680, April.
  278. Ademmer, Martin & Boysen-Hogrefe, Jens & Fiedler, Salomon & Groll, Dominik & Jannsen, Nils & Kooths, Stefan & Potjagailo, Galina & Wolters, Maik H., 2017. "Deutsche Konjunktur im Herbst 2017 - Deutsche Wirtschaft nähert sich der Hochkonjunktur [German Economy Autumn 2017 - German economy approaches boom period]," Kieler Konjunkturberichte 35, Kiel Institute for the World Economy (IfW Kiel).
  279. Baiguo An & Beibei Zhang, 2020. "Logistic regression with image covariates via the combination of L1 and Sobolev regularizations," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-18, June.
  280. Rafael Blanquero & Emilio Carrizosa & Pepa Ramírez-Cobo & M. Remedios Sillero-Denamiel, 2021. "A cost-sensitive constrained Lasso," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(1), pages 121-158, March.
  281. Qianyun Li & Runmin Shi & Faming Liang, 2019. "Drug sensitivity prediction with high-dimensional mixture regression," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-18, February.
  282. Mohamed Trabelsi & Mohamed Massaoudi & Ines Chihi & Lilia Sidhom & Shady S. Refaat & Tingwen Huang & Fakhreddine S. Oueslati, 2022. "An Effective Hybrid Symbolic Regression–Deep Multilayer Perceptron Technique for PV Power Forecasting," Energies, MDPI, vol. 15(23), pages 1-14, November.
  283. Qinqin Hu & Lu Lin, 2022. "Feature Screening in High Dimensional Regression with Endogenous Covariates," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 949-969, October.
  284. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Working Papers 202111, Geary Institute, University College Dublin.
  285. Naoki Hamada & Shunsuke Ichiki, 2022. "Free Disposal Hull Condition to Verify When Efficiency Coincides with Weak Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 192(1), pages 248-270, January.
  286. Huck, Nicolas, 2019. "Large data sets and machine learning: Applications to statistical arbitrage," European Journal of Operational Research, Elsevier, vol. 278(1), pages 330-342.
  287. Sacha Epskamp & Mijke Rhemtulla & Denny Borsboom, 2017. "Generalized Network Psychometrics: Combining Network and Latent Variable Models," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 904-927, December.
  288. Md Showaib Rahman Sarker & Michael Pokojovy & Sangjin Kim, 2019. "On the Performance of Variable Selection and Classification via Rank-Based Classifier," Mathematics, MDPI, vol. 7(5), pages 1-16, May.
  289. Snezhana Gocheva-Ilieva & Iliycho Iliev, 2016. "Using Generalized PathSeeker Regularized Regression for Modeling and Prediction of Output Power of CuBr Laser," Proceedings of International Academic Conferences 4006523, International Institute of Social and Economic Sciences.
  290. Nikodinoska, Dragana & Käso, Mathias & Müsgens, Felix, 2022. "Solar and wind power generation forecasts using elastic net in time-varying forecast combinations," Applied Energy, Elsevier, vol. 306(PA).
  291. Sakae Oya, 2021. "A Bayesian Graphical Approach for Large-Scale Portfolio Management with Fewer Historical Data," Papers 2103.05880, arXiv.org, revised Mar 2022.
  292. Xia, Siwei & Yang, Yuehan & Yang, Hu, 2023. "High-dimensional sparse portfolio selection with nonnegative constraint," Applied Mathematics and Computation, Elsevier, vol. 443(C).
  293. Hirad Baradaran Rezaei & Alireza Amjadian & Mohammad Vahid Sebt & Reza Askari & Abolfazl Gharaei, 2023. "An ensemble method of the machine learning to prognosticate the gastric cancer," Annals of Operations Research, Springer, vol. 328(1), pages 151-192, September.
  294. Zhou, Ding-Xuan, 2013. "On grouping effect of elastic net," Statistics & Probability Letters, Elsevier, vol. 83(9), pages 2108-2112.
  295. Heather E Wheeler & Kaanan P Shah & Jonathon Brenner & Tzintzuni Garcia & Keston Aquino-Michaels & GTEx Consortium & Nancy J Cox & Dan L Nicolae & Hae Kyung Im, 2016. "Survey of the Heritability and Sparse Architecture of Gene Expression Traits across Human Tissues," PLOS Genetics, Public Library of Science, vol. 12(11), pages 1-23, November.
  296. Jung, Yoon Mo & Whang, Joyce Jiyoung & Yun, Sangwoon, 2020. "Sparse probabilistic K-means," Applied Mathematics and Computation, Elsevier, vol. 382(C).
  297. Gang Wang & Feng Zhang & Bayi Cheng & Fang Fang, 2021. "DAMER: a novel diagnosis aggregation method with evidential reasoning rule for bearing fault diagnosis," Journal of Intelligent Manufacturing, Springer, vol. 32(1), pages 1-20, January.
  298. Bondatti, Massimiliano & Rillo, Giovanni, 2022. "Commodity tail-risk and exchange rates," Finance Research Letters, Elsevier, vol. 47(PA).
  299. Friedman, Jerome H., 2012. "Fast sparse regression and classification," International Journal of Forecasting, Elsevier, vol. 28(3), pages 722-738.
  300. Katarina M. Jørgensen & Ellen Færgestad Mosleth & Kristian Hovde Liland & Nancy B. Hopf & Rita Holdhus & Anne-Kristin Stavrum & Bjørn Tore Gjertsen & Jorunn Kirkeleit, 2018. "Gene Expression Response in Peripheral Blood Cells of Petroleum Workers Exposed to Sub-Ppm Benzene Levels," IJERPH, MDPI, vol. 15(11), pages 1-18, October.
  301. Francesco Bloise & Paolo Brunori & Patrizio Piraino, 2021. "Estimating intergenerational income mobility on sub-optimal data: a machine learning approach," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 19(4), pages 643-665, December.
  302. Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2019. "The long-run information effect of central bank communication," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 185-202.
  303. Marica Valente & Timm Gries & Lorenzo Trapani, 2023. "Informal employment from migration shocks," Working Papers 2023-09, Faculty of Economics and Statistics, Universität Innsbruck.
  304. Muniain, Peru & Ziel, Florian, 2020. "Probabilistic forecasting in day-ahead electricity markets: Simulating peak and off-peak prices," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1193-1210.
  305. He Jiang, 2023. "Robust forecasting in spatial autoregressive model with total variation regularization," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 195-211, March.
  306. Joanna Bruzda, 2020. "The wavelet scaling approach to forecasting: Verification on a large set of Noisy data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 353-367, April.
  307. John M. Abowd & Joelle Abramowitz & Margaret C. Levenstein & Kristin McCue & Dhiren Patki & Trivellore Raghunathan & Ann M. Rodgers & Matthew D. Shapiro & Nada Wasi, 2019. "Optimal Probabilistic Record Linkage: Best Practice for Linking Employers in Survey and Administrative Data," Working Papers 19-08, Center for Economic Studies, U.S. Census Bureau.
  308. Ahmad Roumiani & Abdul Basir Arian & Hamide Mahmoodi & Hamid Shayan, 2023. "Estimation and prediction of ecological footprint using tourism development indices top tourist destination countries," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(2), pages 1084-1100, April.
  309. Lu Liu & Junheng Gao & Georgia Beasley & Sin-Ho Jung, 2023. "LASSO and Elastic Net Tend to Over-Select Features," Mathematics, MDPI, vol. 11(17), pages 1-16, August.
  310. Anshul Verma & Orazio Angelini & Tiziana Di Matteo, 2019. "A new set of cluster driven composite development indicators," Papers 1911.11226, arXiv.org, revised Mar 2020.
  311. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
  312. Sarah Cornell-Farrow & Robert Garrard, 2018. "Machine Learning Classifiers Do Not Improve the Prediction of Academic Risk: Evidence from Australia," Papers 1807.07215, arXiv.org, revised Jan 2020.
  313. Liyu Dou & Jakub Kastl & John Lazarev, 2020. "Quantifying Delay Externalities in Airline Networks," Working Papers 2020-65, Princeton University. Economics Department..
  314. Mohan Wang & Pin-Chao Liao, 2023. "Personality Assessment Based on Electroencephalography Signals during Hazard Recognition," Sustainability, MDPI, vol. 15(11), pages 1-16, May.
  315. Araujo, Gustavo Silva & Gaglianone, Wagner Piazza, 2023. "Machine learning methods for inflation forecasting in Brazil: New contenders versus classical models," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(2).
  316. Juan, Aranzazu de & Poncela, Maria Pilar & Ruiz Ortega, Esther, 2023. "Economic activity and C02 emissions in Spain," DES - Working Papers. Statistics and Econometrics. WS 37975, Universidad Carlos III de Madrid. Departamento de Estadística.
  317. Dai, Linlin & Chen, Kani & Sun, Zhihua & Liu, Zhenqiu & Li, Gang, 2018. "Broken adaptive ridge regression and its asymptotic properties," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 334-351.
  318. Kharratzadeh, Milad & Coates, Mark, 2017. "Semi-parametric order-based generalized multivariate regression," Journal of Multivariate Analysis, Elsevier, vol. 156(C), pages 89-102.
  319. Niu, Zibo & Ma, Feng & Zhang, Hongwei, 2022. "The role of uncertainty measures in volatility forecasting of the crude oil futures market before and during the COVID-19 pandemic," Energy Economics, Elsevier, vol. 112(C).
  320. Yufang Wen & Xiangdong Song & Haisen Zhang, 2008. "A New Algorithm in Maximum Likelihood Estimation for Generalized Linear Models," Modern Applied Science, Canadian Center of Science and Education, vol. 2(5), pages 1-86, September.
  321. Minghui Wang & Lingling Yue & Xiaowen Cui & Cheng Chen & Hongyan Zhou & Qin Ma & Bin Yu, 2020. "Prediction of Extracellular Matrix Proteins by Fusing Multiple Feature Information, Elastic Net, and Random Forest Algorithm," Mathematics, MDPI, vol. 8(2), pages 1-18, January.
  322. Jiwoong Kim & David E Greenberg & Reed Pifer & Shuang Jiang & Guanghua Xiao & Samuel A Shelburne & Andrew Koh & Yang Xie & Xiaowei Zhan, 2020. "VAMPr: VAriant Mapping and Prediction of antibiotic resistance via explainable features and machine learning," PLOS Computational Biology, Public Library of Science, vol. 16(1), pages 1-17, January.
  323. Ribeiro, Pinho J., 2017. "Selecting exchange rate fundamentals by bootstrap," International Journal of Forecasting, Elsevier, vol. 33(4), pages 894-914.
  324. Petra Posedel v{S}imovi'c & Davor Horvatic & Edward W. Sun, 2021. "Classifying variety of customer's online engagement for churn prediction with mixed-penalty logistic regression," Papers 2105.07671, arXiv.org, revised Jul 2021.
  325. Changrong Yan & Dixin Zhang, 2013. "Sparse dimension reduction for survival data," Computational Statistics, Springer, vol. 28(4), pages 1835-1852, August.
  326. Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
  327. Felipe Leal & Carlos Molina & Eduardo Zilberman, 2020. "Proyección de la Inflación en Chile con Métodos de Machine Learning," Working Papers Central Bank of Chile 860, Central Bank of Chile.
  328. Kei Hirose & Miyuki Imada, 2018. "Sparse factor regression via penalized maximum likelihood estimation," Statistical Papers, Springer, vol. 59(2), pages 633-662, June.
  329. Larkin Terrie, 2022. "Banff or Simputation? Assessing Alternative Approaches to the Imputation of Missing and Erroneous Data on BEA’s Multinational Enterprise Surveys," BEA Working Papers 0194, Bureau of Economic Analysis.
  330. Gonché Danesh & Victor Virlogeux & Christophe Ramière & Caroline Charre & Laurent Cotte & Samuel Alizon, 2021. "Quantifying transmission dynamics of acute hepatitis C virus infections in a heterogeneous population using sequence data," PLOS Pathogens, Public Library of Science, vol. 17(9), pages 1-19, September.
  331. Aaron Hudson & Ali Shojaie, 2022. "Covariate-Adjusted Inference for Differential Analysis of High-Dimensional Networks," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(1), pages 345-388, June.
  332. Agrawal, Rahul Kumar & Muchahary, Frankle & Tripathi, Madan Mohan, 2019. "Ensemble of relevance vector machines and boosted trees for electricity price forecasting," Applied Energy, Elsevier, vol. 250(C), pages 540-548.
  333. Abdallah Mkhadri & Mohamed Ouhourane, 2015. "A group VISA algorithm for variable selection," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(1), pages 41-60, March.
  334. Ahmed, Walid M.A. & Sleem, Mohamed A.E., 2023. "Short- and long-run determinants of the price behavior of US clean energy stocks: A dynamic ARDL simulations approach," Energy Economics, Elsevier, vol. 124(C).
  335. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2020. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Papers 2012.11649, arXiv.org, revised Jun 2022.
  336. Ling-Tim Wong & Kwok-Wai Mui & Tsz-Wun Tsang, 2022. "Updating Indoor Air Quality (IAQ) Assessment Screening Levels with Machine Learning Models," IJERPH, MDPI, vol. 19(9), pages 1-23, May.
  337. Gang Liu & Hui Yang, 2018. "Self-organizing network for variable clustering," Annals of Operations Research, Springer, vol. 263(1), pages 119-140, April.
  338. Meiyappan, Prasanth & Dalton, Michael & O’Neill, Brian C. & Jain, Atul K., 2014. "Spatial modeling of agricultural land use change at global scale," Ecological Modelling, Elsevier, vol. 291(C), pages 152-174.
  339. Ju, Xiaomeng & Salibián-Barrera, Matías, 2021. "Robust boosting for regression problems," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
  340. Xue-Jun Ma & Jing-Xiao Zhang, 2016. "A new variable selection approach for varying coefficient models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(1), pages 59-72, January.
  341. Maur,Jean-Christophe & Nedeljkovic,Milan & Von Uexkull,Jan Erik, 2022. "FDI and Trade Outcomes at the Industry Level—A Data-Driven Approach," Policy Research Working Paper Series 9901, The World Bank.
  342. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
  343. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Exchange Rates under Model and Parameter Uncertainty," CQE Working Papers 3214, Center for Quantitative Economics (CQE), University of Muenster.
  344. Fitzpatrick, Trevor & Mues, Christophe, 2021. "How can lenders prosper? Comparing machine learning approaches to identify profitable peer-to-peer loan investments," European Journal of Operational Research, Elsevier, vol. 294(2), pages 711-722.
  345. Hendrik van der Wurp & Andreas Groll, 2023. "Introducing LASSO-type penalisation to generalised joint regression modelling for count data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 127-151, March.
  346. Ching Hsu & Tina Yu & Shu-Heng Chen, 2021. "Narrative economics using textual analysis of newspaper data: new insights into the U.S. Silver Purchase Act and Chinese price level in 1928–1936," Journal of Computational Social Science, Springer, vol. 4(2), pages 761-785, November.
  347. Lukasz Huminiecki, 2018. "Modelling of the breadth of expression from promoter architectures identifies pro-housekeeping transcription factors," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-28, June.
  348. Qing Wang & Dan Zhao, 2019. "Penalization methods with group-wise sparsity: econometric applications to eBay Motors online auctions," Empirical Economics, Springer, vol. 57(2), pages 683-704, August.
  349. Shih-Chih Chen & Jianing Hou & De Xiao, 2018. "“One Belt, One Road” Initiative to Stimulate Trade in China: A Counter-Factual Analysis," Sustainability, MDPI, vol. 10(9), pages 1-13, September.
  350. Zander S. Venter & Adam Sadilek & Charlotte Stanton & David N. Barton & Kristin Aunan & Sourangsu Chowdhury & Aaron Schneider & Stefano Maria Iacus, 2021. "Mobility in Blue-Green Spaces Does Not Predict COVID-19 Transmission: A Global Analysis," IJERPH, MDPI, vol. 18(23), pages 1-12, November.
  351. Oguzhan Cepni & Rangan Gupta & Yigit Onay, 2022. "The role of investor sentiment in forecasting housing returns in China: A machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1725-1740, December.
  352. Julius Stakenas, 2012. "Generating short-term forecasts of the Lithuanian GDP using factor models," Bank of Lithuania Working Paper Series 13, Bank of Lithuania.
  353. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
  354. Ellington, Michael & Stamatogiannis, Michalis P. & Zheng, Yawen, 2022. "A study of cross-industry return predictability in the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 83(C).
  355. Zhixuan Fu & Chirag R. Parikh & Bingqing Zhou, 2017. "Penalized variable selection in competing risks regression," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(3), pages 353-376, July.
  356. Tian, Yuzhu & Song, Xinyuan, 2020. "Bayesian bridge-randomized penalized quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
  357. Yu-Zhu Tian & Man-Lai Tang & Mao-Zai Tian, 2021. "Bayesian joint inference for multivariate quantile regression model with L $$_{1/2}$$ 1 / 2 penalty," Computational Statistics, Springer, vol. 36(4), pages 2967-2994, December.
  358. Samuel Shamiri & Leanne Ngai & Peter Lake & Yin Shan & Amee McMillan & Therese Smith & Kishor Sharma, 2022. "Nowcasting the Australian Labour Market at Disaggregated Levels," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 55(3), pages 389-404, September.
  359. Kenneth Lange & Eric C. Chi & Hua Zhou, 2014. "A Brief Survey of Modern Optimization for Statisticians," International Statistical Review, International Statistical Institute, vol. 82(1), pages 46-70, April.
  360. Koo, Bonsoo & Anderson, Heather M. & Seo, Myung Hwan & Yao, Wenying, 2020. "High-dimensional predictive regression in the presence of cointegration," Journal of Econometrics, Elsevier, vol. 219(2), pages 456-477.
  361. Florian Ziel, 2015. "Iteratively reweighted adaptive lasso for conditional heteroscedastic time series with applications to AR-ARCH type processes," Papers 1502.06557, arXiv.org, revised Dec 2015.
  362. Lu, Zhaosong & Pong, Ting Kei & Zhang, Yong, 2012. "An alternating direction method for finding Dantzig selectors," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4037-4046.
  363. Lee, Hahn Shik & Lee, Woo Suk, 2019. "Cross-regional connectedness in the Korean housing market," Journal of Housing Economics, Elsevier, vol. 46(C).
  364. Lore Zumeta-Olaskoaga & Maximilian Weigert & Jon Larruskain & Eder Bikandi & Igor Setuain & Josean Lekue & Helmut Küchenhoff & Dae-Jin Lee, 2023. "Prediction of sports injuries in football: a recurrent time-to-event approach using regularized Cox models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 101-126, March.
  365. G. S. Monti & P. Filzmoser, 2022. "Robust logistic zero-sum regression for microbiome compositional data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(2), pages 301-324, June.
  366. Michael Greenacre & Patrick J. F Groenen & Trevor Hastie & Alfonso Iodice d’Enza & Angelos Markos & Elena Tuzhilina, 2023. "Principal component analysis," Economics Working Papers 1856, Department of Economics and Business, Universitat Pompeu Fabra.
  367. Hongxin Zhao & Lingchen Kong & Hou-Duo Qi, 2021. "Optimal portfolio selections via $$\ell _{1, 2}$$ ℓ 1 , 2 -norm regularization," Computational Optimization and Applications, Springer, vol. 80(3), pages 853-881, December.
  368. Kristian Bjørn Hessellund & Ganggang Xu & Yongtao Guan & Rasmus Waagepetersen, 2022. "Second‐order semi‐parametric inference for multivariate log Gaussian Cox processes," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(1), pages 244-268, January.
  369. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  370. Lionel Roger, 2018. "Blinded by the light? Heterogeneity in the luminosity-growth nexus and the African growth miracle," Discussion Papers 2018-04, University of Nottingham, CREDIT.
  371. Norman R. Swanson & Weiqi Xiong, 2018. "Big data analytics in economics: What have we learned so far, and where should we go from here?," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 51(3), pages 695-746, August.
  372. Anastasis Kratsios & Cody Hyndman, 2018. "NEU: A Meta-Algorithm for Universal UAP-Invariant Feature Representation," Papers 1809.00082, arXiv.org, revised May 2021.
  373. Sauvenier, Mathieu & Van Bellegem, Sébastien, 2023. "Goodness-of-fit test in high-dimensional linear sparse models," LIDAM Discussion Papers CORE 2023008, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  374. Sara Agaba & Chiara Ferré & Marco Musetti & Roberto Comolli, 2024. "Mapping Soil Organic Carbon Stock and Uncertainties in an Alpine Valley (Northern Italy) Using Machine Learning Models," Land, MDPI, vol. 13(1), pages 1-16, January.
  375. Ali Mahzarnia & Jun Song, 2022. "Multivariate functional group sparse regression: Functional predictor selection," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-22, April.
  376. Li, Siqing & Ling, Leevan & Cheung, Ka Chun, 2019. "Discrete least-squares radial basis functions approximations," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 542-552.
  377. Scutari, Marco & Panero, Francesca & Proissl, Manuel, 2022. "Achieving fairness with a simple ridge penalty," LSE Research Online Documents on Economics 116916, London School of Economics and Political Science, LSE Library.
  378. Sweata Sen & Damitri Kundu & Kiranmoy Das, 2023. "Variable selection for categorical response: a comparative study," Computational Statistics, Springer, vol. 38(2), pages 809-826, June.
  379. Oliver J. Rutz & Michael Trusov & Randolph E. Bucklin, 2011. "Modeling Indirect Effects of Paid Search Advertising: Which Keywords Lead to More Future Visits?," Marketing Science, INFORMS, vol. 30(4), pages 646-665, July.
  380. Fan, Jianqing & Liao, Yuan, 2012. "Endogeneity in ultrahigh dimension," MPRA Paper 38698, University Library of Munich, Germany.
  381. Juan C. Laria & M. Carmen Aguilera-Morillo & Enrique Álvarez & Rosa E. Lillo & Sara López-Taruella & María del Monte-Millán & Antonio C. Picornell & Miguel Martín & Juan Romo, 2021. "Iterative Variable Selection for High-Dimensional Data: Prediction of Pathological Response in Triple-Negative Breast Cancer," Mathematics, MDPI, vol. 9(3), pages 1-14, January.
  382. Shiqiang Jin & Gyuhyeong Goh, 2021. "Bayesian selection of best subsets via hybrid search," Computational Statistics, Springer, vol. 36(3), pages 1991-2007, September.
  383. Kubus Mariusz, 2016. "Assessment of Predictor Importance with the Example of the Real Estate Market," Folia Oeconomica Stetinensia, Sciendo, vol. 16(2), pages 29-39, December.
  384. A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2018. "A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High‐Dimensional Linear Regression Models," Econometrica, Econometric Society, vol. 86(4), pages 1479-1512, July.
  385. Yucheng Yang & Yue Pang & Guanhua Huang & Weinan E, 2020. "The Knowledge Graph for Macroeconomic Analysis with Alternative Big Data," Papers 2010.05172, arXiv.org.
  386. Hui Xiao & Yiguo Sun, 2019. "On Tuning Parameter Selection in Model Selection and Model Averaging: A Monte Carlo Study," JRFM, MDPI, vol. 12(3), pages 1-16, June.
  387. Engler David & Li Yi, 2009. "Survival Analysis with High-Dimensional Covariates: An Application in Microarray Studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-22, February.
  388. Jin-Kyu Jung & Manasa Patnam & Anna Ter-Martirosyan, 2018. "An Algorithmic Crystal Ball: Forecasts-based on Machine Learning," IMF Working Papers 2018/230, International Monetary Fund.
  389. Gareth M. James & Peter Radchenko & Jinchi Lv, 2009. "DASSO: connections between the Dantzig selector and lasso," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(1), pages 127-142, January.
  390. Alex Coad & Stjepan Srhoj, 2020. "Catching Gazelles with a Lasso: Big data techniques for the prediction of high-growth firms," Small Business Economics, Springer, vol. 55(3), pages 541-565, October.
  391. Zhifeng Dai & Tingyu Li & Mi Yang, 2022. "Forecasting stock return volatility: The role of shrinkage approaches in a data‐rich environment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 980-996, August.
  392. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
  393. Hongjin He & Xingju Cai & Deren Han, 2015. "A fast splitting method tailored for Dantzig selector," Computational Optimization and Applications, Springer, vol. 62(2), pages 347-372, November.
  394. Massimo Ferrari Minesso & Frederik Kurcz & Maria Sole Pagliari, 2022. "Do words hurt more than actions? The impact of trade tensions on financial markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1138-1159, September.
  395. Masakazu Agetsuma & Issei Sato & Yasuhiro R. Tanaka & Luis Carrillo-Reid & Atsushi Kasai & Atsushi Noritake & Yoshiyuki Arai & Miki Yoshitomo & Takashi Inagaki & Hiroshi Yukawa & Hitoshi Hashimoto & J, 2023. "Activity-dependent organization of prefrontal hub-networks for associative learning and signal transformation," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
  396. Petra P. Šimović & Claire Y. T. Chen & Edward W. Sun, 2023. "Classifying the Variety of Customers’ Online Engagement for Churn Prediction with a Mixed-Penalty Logistic Regression," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 451-485, January.
  397. Soave, David & Lawless, Jerald F., 2023. "Regularized regression for two phase failure time studies," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
  398. Messner, Jakob W. & Pinson, Pierre, 2019. "Online adaptive lasso estimation in vector autoregressive models for high dimensional wind power forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1485-1498.
  399. Yunquan Song & Zitong Li & Minglu Fang, 2022. "Robust Variable Selection Based on Penalized Composite Quantile Regression for High-Dimensional Single-Index Models," Mathematics, MDPI, vol. 10(12), pages 1-17, June.
  400. Lasanthi C. R. Pelawa Watagoda & David J. Olive, 2021. "Comparing six shrinkage estimators with large sample theory and asymptotically optimal prediction intervals," Statistical Papers, Springer, vol. 62(5), pages 2407-2431, October.
  401. Boriss Siliverstovs, 2015. "Dissecting the purchasing managers' index," KOF Working papers 15-376, KOF Swiss Economic Institute, ETH Zurich.
  402. Jingxuan Luo & Lili Yue & Gaorong Li, 2023. "Overview of High-Dimensional Measurement Error Regression Models," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
  403. Huang, Qiming & Zhu, Yu, 2016. "Model-free sure screening via maximum correlation," Journal of Multivariate Analysis, Elsevier, vol. 148(C), pages 89-106.
  404. Härdle, Wolfgang Karl & Chen, Shi & Liang, Chong & Schienle, Melanie, 2018. "Time-varying Limit Order Book Networks," IRTG 1792 Discussion Papers 2018-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  405. Joshua Mitts, 2020. "Short and Distort," The Journal of Legal Studies, University of Chicago Press, vol. 49(2), pages 287-334.
  406. Xiaoguang Xu & Chachrit Khunsriraksakul & James M. Eales & Sebastien Rubin & David Scannali & Sushant Saluja & David Talavera & Havell Markus & Lida Wang & Maciej Drzal & Akhlaq Maan & Abigail C. Lay , 2024. "Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets," Nature Communications, Nature, vol. 15(1), pages 1-29, December.
  407. James T. E. Chapman & Ajit Desai, 2023. "Macroeconomic Predictions Using Payments Data and Machine Learning," Forecasting, MDPI, vol. 5(4), pages 1-32, November.
  408. Kamil Yilmaz, 2018. "Bank Volatility Connectedness in South East Asia," Koç University-TUSIAD Economic Research Forum Working Papers 1807, Koc University-TUSIAD Economic Research Forum.
  409. Davood Hajinezhad & Qingjiang Shi, 2018. "Alternating direction method of multipliers for a class of nonconvex bilinear optimization: convergence analysis and applications," Journal of Global Optimization, Springer, vol. 70(1), pages 261-288, January.
  410. Christian Gross & Pierre L. Siklos, 2020. "Analyzing credit risk transmission to the nonfinancial sector in Europe: A network approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 61-81, January.
  411. Marco S. Reis & Ricardo Rendall & Biagio Palumbo & Antonio Lepore & Christian Capezza, 2020. "Predicting ships' CO2 emissions using feature‐oriented methods," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(1), pages 110-123, January.
  412. Yuuki Yokoyama & Tomu Katsumata & Muneki Yasuda, 2019. "Restricted Boltzmann Machine with Multivalued Hidden Variables," The Review of Socionetwork Strategies, Springer, vol. 13(2), pages 253-266, October.
  413. Pushan Dutt & Ilia Tsetlin, 2021. "Income distribution and economic development: Insights from machine learning," Economics and Politics, Wiley Blackwell, vol. 33(1), pages 1-36, March.
  414. Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
  415. Samuel D. Lendle & Meenakshi S. Subbaraman & Mark J. van der Laan, 2013. "Identification and Efficient Estimation of the Natural Direct Effect among the Untreated," Biometrics, The International Biometric Society, vol. 69(2), pages 310-317, June.
  416. Afanasyev, Dmitriy O. & Fedorova, Elena & Ledyaeva, Svetlana, 2021. "Strength of words: Donald Trump's tweets, sanctions and Russia's ruble," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 253-277.
  417. Cheng, Xian & Wu, Peng & Liao, Stephen Shaoyi & Wang, Xuelian, 2023. "An integrated model for crude oil forecasting: Causality assessment and technical efficiency," Energy Economics, Elsevier, vol. 117(C).
  418. Ciner, Cetin, 2019. "Do industry returns predict the stock market? A reprise using the random forest," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 152-158.
  419. Zhi Zhao & Manuela Zucknick, 2020. "Structured penalized regression for drug sensitivity prediction," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(3), pages 525-545, June.
  420. Tyler A Joseph & Liat Shenhav & Joao B Xavier & Eran Halperin & Itsik Pe’er, 2020. "Compositional Lotka-Volterra describes microbial dynamics in the simplex," PLOS Computational Biology, Public Library of Science, vol. 16(5), pages 1-22, May.
  421. Yue Huang & Xuezhi Sun & Guangshu Hu, 2011. "An integrated genetics approach for identifying protein signal pathways of Alzheimer's disease," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 14(04), pages 371-378.
  422. Julien Sainte-Marie & Paul-Henry Cournède, 2019. "Insights of Global Sensitivity Analysis in Biological Models with Dependent Parameters," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(1), pages 92-111, March.
  423. Sriubaite, I. & Harris, A. & Jones, A.M. & Gabbe, B., 2020. "Economic Consequences of Road Traffic Injuries. Application of the Super Learner algorithm," Health, Econometrics and Data Group (HEDG) Working Papers 20/20, HEDG, c/o Department of Economics, University of York.
  424. Wang, Jiqian & Ma, Feng & Bouri, Elie & Zhong, Juandan, 2022. "Volatility of clean energy and natural gas, uncertainty indices, and global economic conditions," Energy Economics, Elsevier, vol. 108(C).
  425. Bennedsen, Mikkel & Hillebrand, Eric & Koopman, Siem Jan, 2021. "Modeling, forecasting, and nowcasting U.S. CO2 emissions using many macroeconomic predictors," Energy Economics, Elsevier, vol. 96(C).
  426. Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2022. "Making text count: Economic forecasting using newspaper text," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 896-919, August.
  427. Immanuel Bayer & Philip Groth & Sebastian Schneckener, 2013. "Prediction Errors in Learning Drug Response from Gene Expression Data – Influence of Labeling, Sample Size, and Machine Learning Algorithm," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-13, July.
  428. Lê Cao Kim-Anh & Rossouw Debra & Robert-Granié Christèle & Besse Philippe, 2008. "A Sparse PLS for Variable Selection when Integrating Omics Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(1), pages 1-32, November.
  429. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore & Wing-Keung Wong, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
  430. Laura Freijeiro‐González & Manuel Febrero‐Bande & Wenceslao González‐Manteiga, 2022. "A Critical Review of LASSO and Its Derivatives for Variable Selection Under Dependence Among Covariates," International Statistical Review, International Statistical Institute, vol. 90(1), pages 118-145, April.
  431. David Guirguis & Conrad Tucker & Jack Beuth, 2024. "Accelerating process development for 3D printing of new metal alloys," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  432. Yongjin Li & Qingzhao Zhang & Qihua Wang, 2017. "Penalized estimation equation for an extended single-index model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 169-187, February.
  433. Randy Carter & Netsanet Michael, 2022. "Factor Analysis Regression for Predictive Modeling with High-Dimensional Data," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 115-132, September.
  434. Wenyan Zhong & Xuewen Lu & Jingjing Wu, 2021. "Bi-level variable selection in semiparametric transformation models with right-censored data," Computational Statistics, Springer, vol. 36(3), pages 1661-1692, September.
  435. Caravaggio, Nicola & Resce, Giuliano, 2023. "Enhancing Healthcare Cost Forecasting: A Machine Learning Model for Resource Allocation in Heterogeneous Regions," Economics & Statistics Discussion Papers esdp23090, University of Molise, Department of Economics.
  436. Moharil Janhavi & May Paul & Gaile Daniel P. & Blair Rachael Hageman, 2016. "Belief propagation in genotype-phenotype networks," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 15(1), pages 39-53, March.
  437. Jiang, Liewen & Bondell, Howard D. & Wang, Huixia Judy, 2014. "Interquantile shrinkage and variable selection in quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 208-219.
  438. Yazan Abdel Majeed & Saria S Awadalla & James L Patton, 2018. "Regression techniques employing feature selection to predict clinical outcomes in stroke," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-17, October.
  439. Wei-han Liu, 2013. "Lunar calendar effect: evidence of the Chinese Farmer's Calendar on the equity markets in East Asia," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 18(4), pages 560-593.
  440. Tian, Guangning & Peng, Yuchao & Meng, Yuhao, 2023. "Forecasting crude oil prices in the COVID-19 era: Can machine learn better?," Energy Economics, Elsevier, vol. 125(C).
  441. Camilla Beck Olsen & Hans Olav Melberg, 2018. "Did adolescents in Norway respond to the elimination of copayments for general practitioner services?," Health Economics, John Wiley & Sons, Ltd., vol. 27(7), pages 1120-1130, July.
  442. Mariusz Kubus, 2016. "Locally Regularized Linear Regression in the Valuation of Real Estate," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 17(3), pages 515-524, September.
  443. Sharma, Amandeep & Kakkar, Ajay, 2018. "Forecasting daily global solar irradiance generation using machine learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2254-2269.
  444. Anindya Bhadra & Bani K. Mallick, 2013. "Joint High-Dimensional Bayesian Variable and Covariance Selection with an Application to eQTL Analysis," Biometrics, The International Biometric Society, vol. 69(2), pages 447-457, June.
  445. Nikolay Iskrev, 2010. "Evaluating the strength of identification in DSGE models. An a priori approach," 2010 Meeting Papers 1117, Society for Economic Dynamics.
  446. Satopää, Ville A. & Salikhov, Marat & Tetlock, Philip E. & Mellers, Barbara, 2023. "Decomposing the effects of crowd-wisdom aggregators: The bias–information–noise (BIN) model," International Journal of Forecasting, Elsevier, vol. 39(1), pages 470-485.
  447. Hidetoshi Matsui & Toshihiro Misumi, 2015. "Variable selection for varying-coefficient models with the sparse regularization," Computational Statistics, Springer, vol. 30(1), pages 43-55, March.
  448. Halewijn M. Drent & Barbara van den Hoofdakker & Jan K. Buitelaar & Pieter J. Hoekstra & Andrea Dietrich, 2022. "Factors Related to Perceived Stigma in Parents of Children and Adolescents in Outpatient Mental Healthcare," IJERPH, MDPI, vol. 19(19), pages 1-14, October.
  449. Daan Kolkman & Arjen van Witteloostuijn, 2019. "Data Science in Strategy: Machine learning and text analysis in the study of firm growth," Tinbergen Institute Discussion Papers 19-066/VI, Tinbergen Institute.
  450. John A. Major, 2019. "Methodological Considerations in the Statistical Modeling of Catastrophe Bond Prices," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 22(1), pages 39-56, March.
  451. Yazhao Lv & Riquan Zhang & Weihua Zhao & Jicai Liu, 2014. "Quantile regression and variable selection for the single-index model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(7), pages 1565-1577, July.
  452. Ruggieri, Eric & Lawrence, Charles E., 2012. "On efficient calculations for Bayesian variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1319-1332.
  453. Loann David Denis Desboulets, 2018. "A Review on Variable Selection in Regression Analysis," Econometrics, MDPI, vol. 6(4), pages 1-27, November.
  454. Parminder K Mankoo & Ronglai Shen & Nikolaus Schultz & Douglas A Levine & Chris Sander, 2011. "Time to Recurrence and Survival in Serous Ovarian Tumors Predicted from Integrated Genomic Profiles," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-12, November.
  455. Khan Md Hasinur Rahaman & Bhadra Anamika & Howlader Tamanna, 2019. "Stability selection for lasso, ridge and elastic net implemented with AFT models," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 18(5), pages 1-14, October.
  456. Juan Tenorio & Wilder Perez, 2024. "Monthly GDP nowcasting with Machine Learning and Unstructured Data," Papers 2402.04165, arXiv.org.
  457. Shaomin Li & Haoyu Wei & Xiaoyu Lei, 2022. "Heterogeneous Overdispersed Count Data Regressions via Double-Penalized Estimations," Mathematics, MDPI, vol. 10(10), pages 1-25, May.
  458. Daniel Borup & David E. Rapach & Erik Christian Montes Schütte, 2021. "Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data," CREATES Research Papers 2021-02, Department of Economics and Business Economics, Aarhus University.
  459. Lai, Peng & Song, Fengli & Chen, Kaiwen & Liu, Zhi, 2017. "Model free feature screening with dependent variable in ultrahigh dimensional binary classification," Statistics & Probability Letters, Elsevier, vol. 125(C), pages 141-148.
  460. Won Hee Lee, 2023. "The Choice of Machine Learning Algorithms Impacts the Association between Brain-Predicted Age Difference and Cognitive Function," Mathematics, MDPI, vol. 11(5), pages 1-15, March.
  461. Jian Huang & Shuangge Ma & Huiliang Xie, 2006. "Regularized Estimation in the Accelerated Failure Time Model with High-Dimensional Covariates," Biometrics, The International Biometric Society, vol. 62(3), pages 813-820, September.
  462. Daniel Preoţiuc-Pietro & Svitlana Volkova & Vasileios Lampos & Yoram Bachrach & Nikolaos Aletras, 2015. "Studying User Income through Language, Behaviour and Affect in Social Media," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-17, September.
  463. Marcelo C. Medeiros & Eduardo F. Mendes, 2015. "l1-Regularization of High-Dimensional Time-Series Models with Flexible Innovations," Textos para discussão 636, Department of Economics PUC-Rio (Brazil).
  464. Mostafa Rezaei & Ivor Cribben & Michele Samorani, 2021. "A clustering-based feature selection method for automatically generated relational attributes," Annals of Operations Research, Springer, vol. 303(1), pages 233-263, August.
  465. Greenwood-Nimmo, Matthew & Huang, Jingong & Nguyen, Viet Hoang, 2019. "Financial sector bailouts, sovereign bailouts, and the transfer of credit risk," Journal of Financial Markets, Elsevier, vol. 42(C), pages 121-142.
  466. Jiangong Zhu & Yixiu Wang & Yuan Huang & R. Bhushan Gopaluni & Yankai Cao & Michael Heere & Martin J. Mühlbauer & Liuda Mereacre & Haifeng Dai & Xinhua Liu & Anatoliy Senyshyn & Xuezhe Wei & Michael K, 2022. "Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
  467. Chetan Badgujar & Sanjoy Das & Dania Martinez Figueroa & Daniel Flippo, 2023. "Application of Computational Intelligence Methods in Agricultural Soil–Machine Interaction: A Review," Agriculture, MDPI, vol. 13(2), pages 1-39, January.
  468. Aspremont Alexandre & Ben Arous Simon & Bricongne Jean-Charles & Lietti Benjamin & Meunier Baptiste, 2023. "Satellites Turn “Concrete”: Tracking Cement with Satellite Data and Neural Networks," Working papers 916, Banque de France.
  469. Olivier Collignon & Jeongseop Han & Hyungmi An & Seungyoung Oh & Youngjo Lee, 2018. "Comparison of the modified unbounded penalty and the LASSO to select predictive genes of response to chemotherapy in breast cancer," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-15, October.
  470. Niaz Muhammad Shahani & Barkat Ullah & Kausar Sultan Shah & Fawad Ul Hassan & Rashid Ali & Mohamed Abdelghany Elkotb & Mohamed E. Ghoneim & Elsayed M. Tag-Eldin, 2022. "Predicting Angle of Internal Friction and Cohesion of Rocks Based on Machine Learning Algorithms," Mathematics, MDPI, vol. 10(20), pages 1-17, October.
  471. Heigle, Julia & Pfeiffer, Friedhelm, 2020. "Langfristige Wirkungen eines nicht abgeschlossenen Studiums auf individuelle Arbeitsmarktergebnisse und die allgemeine Lebenszufriedenheit," ZEW Discussion Papers 20-004, ZEW - Leibniz Centre for European Economic Research.
  472. Alessandro V. M. Oliveira & Bruno F. Oliveira & Moises D. Vassallo, 2024. "Airport service quality perception and flight delays: examining the influence of psychosituational latent traits of respondents in passenger satisfaction surveys," Papers 2401.02139, arXiv.org.
  473. Jiawei Wang & Zhen Chen, 2023. "Exploring Low-Risk Anomalies: A Dynamic CAPM Utilizing a Machine Learning Approach," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
  474. Yang, Hu & Yi, Danhui, 2015. "Studies of the adaptive network-constrained linear regression and its application," Computational Statistics & Data Analysis, Elsevier, vol. 92(C), pages 40-52.
  475. Xiangyu Wang & Chenlei Leng, 2016. "High dimensional ordinary least squares projection for screening variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 589-611, June.
  476. Mingshu Wang & Floris Vermeulen, 2021. "Life between buildings from a street view image: What do big data analytics reveal about neighbourhood organisational vitality?," Urban Studies, Urban Studies Journal Limited, vol. 58(15), pages 3118-3139, November.
  477. Rummens, Anneleen & Hardyns, Wim, 2021. "The effect of spatiotemporal resolution on predictive policing model performance," International Journal of Forecasting, Elsevier, vol. 37(1), pages 125-133.
  478. Qingguo Tang & R. J. Karunamuni, 2018. "Robust variable selection for finite mixture regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(3), pages 489-521, June.
  479. Li, Jiahan & Chen, Weiye, 2014. "Forecasting macroeconomic time series: LASSO-based approaches and their forecast combinations with dynamic factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 996-1015.
  480. Kun Chen & Kung-Sik Chan & Nils Chr. Stenseth, 2014. "Source-Sink Reconstruction Through Regularized Multicomponent Regression Analysis-With Application to Assessing Whether North Sea Cod Larvae Contributed to Local Fjord Cod in Skagerrak," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 560-573, June.
  481. Zhiyu Quan & Changyue Hu & Panyi Dong & Emiliano A. Valdez, 2024. "Improving Business Insurance Loss Models by Leveraging InsurTech Innovation," Papers 2401.16723, arXiv.org.
  482. Krampe, J. & Paparoditis, E. & Trenkler, C., 2023. "Structural inference in sparse high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 234(1), pages 276-300.
  483. Bayer, Sebastian, 2018. "Combining Value-at-Risk forecasts using penalized quantile regressions," Econometrics and Statistics, Elsevier, vol. 8(C), pages 56-77.
  484. Chen, Shunjie & Yang, Sijia & Wang, Pei & Xue, Liugen, 2023. "Two-stage penalized algorithms via integrating prior information improve gene selection from omics data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
  485. Alicia Guillien & Solène Cadiou & Rémy Slama & Valérie Siroux, 2021. "The Exposome Approach to Decipher the Role of Multiple Environmental and Lifestyle Determinants in Asthma," IJERPH, MDPI, vol. 18(3), pages 1-14, January.
  486. Liu, Guangqiang & Guo, Xiaozhu, 2022. "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, vol. 75(C).
  487. Mohammad Amin Amani & Mohammad Mahdi Nasiri, 2023. "A novel cross docking system for distributing the perishable products considering preemption: a machine learning approach," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-32, July.
  488. Wang, Xiaoming & Park, Taesung & Carriere, K.C., 2010. "Variable selection via combined penalization for high-dimensional data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 54(10), pages 2230-2243, October.
  489. Alexander Kirpich & Elizabeth A Ainsworth & Jessica M Wedow & Jeremy R B Newman & George Michailidis & Lauren M McIntyre, 2018. "Variable selection in omics data: A practical evaluation of small sample sizes," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-19, June.
  490. Kim, Hyun Hak & Swanson, Norman R., 2014. "Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence," Journal of Econometrics, Elsevier, vol. 178(P2), pages 352-367.
  491. Ardia, David & Bluteau, Keven & Boudt, Kris, 2019. "Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1370-1386.
  492. Heiss, Florian & Hetzenecker, Stephan & Osterhaus, Maximilian, 2022. "Nonparametric estimation of the random coefficients model: An elastic net approach," Journal of Econometrics, Elsevier, vol. 229(2), pages 299-321.
  493. Nott, David J., 2008. "Predictive performance of Dirichlet process shrinkage methods in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3658-3669, March.
  494. Bonaccolto, Giovanni & Borri, Nicola & Consiglio, Andrea, 2023. "Breakup and default risks in the great lockdown," Journal of Banking & Finance, Elsevier, vol. 147(C).
  495. Lassance, Nathan, 2023. "An analytical shrinkage estimator for linear regression," Statistics & Probability Letters, Elsevier, vol. 194(C).
  496. Nava Ehsan & Bence M. Kotis & Stephane E. Castel & Eric J. Song & Nicholas Mancuso & Pejman Mohammadi, 2024. "Haplotype-aware modeling of cis-regulatory effects highlights the gaps remaining in eQTL data," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
  497. Ten,Gi Khan & Merfeld,Joshua David & Hirfrfot,Kibrom Tafere & Newhouse,David Locke & Pape,Utz Johann, 2022. "How Well Can Real-Time Indicators Track the Economic Impacts of a Crisis Like COVID-19 ?," Policy Research Working Paper Series 10080, The World Bank.
  498. Claudia Wigmann & Anke Hüls & Jean Krutmann & Tamara Schikowski, 2022. "Estimating the Relative Contribution of Environmental and Genetic Risk Factors to Different Aging Traits by Combining Correlated Variables into Weighted Risk Scores," IJERPH, MDPI, vol. 19(24), pages 1-13, December.
  499. Nathaniel E. Helwig, 2022. "Robust Permutation Tests for Penalized Splines," Stats, MDPI, vol. 5(3), pages 1-18, September.
  500. Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2023. "Which COVID-19 information really impacts stock markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
  501. Gustavo A. Alonso-Silverio & Víctor Francisco-García & Iris P. Guzmán-Guzmán & Elías Ventura-Molina & Antonio Alarcón-Paredes, 2021. "Toward Non-Invasive Estimation of Blood Glucose Concentration: A Comparative Performance," Mathematics, MDPI, vol. 9(20), pages 1-13, October.
  502. Heewon Park & Sadanori Konishi, 2020. "Sparse common component analysis for multiple high-dimensional datasets via noncentered principal component analysis," Statistical Papers, Springer, vol. 61(6), pages 2283-2311, December.
  503. Hinrichs, Nils & Kolbe, Jens & Werwatz, Axel, 2020. "AVM and high dimensional data: Do ridge, the lasso or the elastic net provide an "automated" solution?," FORLand Working Papers 22 (2020), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
  504. Christopher Kath & Florian Ziel, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Papers 1811.08604, arXiv.org.
  505. Kim, Nam-Hwui & Browne, Ryan P., 2021. "In the pursuit of sparseness: A new rank-preserving penalty for a finite mixture of factor analyzers," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).
  506. Elias Chaibub Neto & J Christopher Bare & Adam A Margolin, 2014. "Simulation Studies as Designed Experiments: The Comparison of Penalized Regression Models in the “Large p, Small n” Setting," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-21, October.
  507. Kang, Xiaoning & Kang, Lulu & Chen, Wei & Deng, Xinwei, 2022. "A generative approach to modeling data with quantitative and qualitative responses," Journal of Multivariate Analysis, Elsevier, vol. 190(C).
  508. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
  509. Christophe Piette, 2016. "Predicting Belgium’s GDP using targeted bridge models," Working Paper Research 290, National Bank of Belgium.
  510. Aderhold Andrej & Husmeier Dirk & Grzegorczyk Marco, 2014. "Statistical inference of regulatory networks for circadian regulation," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(3), pages 1-47, June.
  511. Dai, Zhifeng & Tang, Rui & Zhang, Xinhua, 2023. "Multilayer network analysis for measuring the inter-connectedness between the oil market and G20 stock markets," Energy Economics, Elsevier, vol. 120(C).
  512. Schumacher, Christian, 2010. "Factor forecasting using international targeted predictors: The case of German GDP," Economics Letters, Elsevier, vol. 107(2), pages 95-98, May.
  513. Mike K. P. So & Wing Ki Liu & Amanda M. Y. Chu, 2018. "Bayesian Shrinkage Estimation Of Time-Varying Covariance Matrices In Financial Time Series," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 369-404, December.
  514. Ana-Maria Zamfir & Adriana AnaMaria Davidescu & Cristina Mocanu, 2022. "Predictors of Economic Outcomes among Romanian Youth: The Influence of Education—An Empirical Approach Based on Elastic Net Regression," IJERPH, MDPI, vol. 19(15), pages 1-15, July.
  515. Li, Hong & Porth, Lysa & Tan, Ken Seng & Zhu, Wenjun, 2021. "Improved index insurance design and yield estimation using a dynamic factor forecasting approach," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 208-221.
  516. Martinez Josue G. & Carroll Raymond J & Muller Samuel & Sampson Joshua N. & Chatterjee Nilanjan, 2010. "A Note on the Effect on Power of Score Tests via Dimension Reduction by Penalized Regression under the Null," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-14, March.
  517. Pei Wang & Dennis L. Chao & Li Hsu, 2011. "Learning Oncogenic Pathways from Binary Genomic Instability Data," Biometrics, The International Biometric Society, vol. 67(1), pages 164-173, March.
  518. Mirshani, Ardalan & Reimherr, Matthew, 2021. "Adaptive function-on-scalar regression with a smoothing elastic net," Journal of Multivariate Analysis, Elsevier, vol. 185(C).
  519. Jinsong Yu & Baohua Mo & Diyin Tang & Jie Yang & Jiuqing Wan & Jingjing Liu, 2017. "Indirect State-of-Health Estimation for Lithium-Ion Batteries under Randomized Use," Energies, MDPI, vol. 10(12), pages 1-19, December.
  520. Karim Barigou & Stéphane Loisel & Yahia Salhi, 2020. "Parsimonious Predictive Mortality Modeling by Regularization and Cross-Validation with and without Covid-Type Effect," Risks, MDPI, vol. 9(1), pages 1-18, December.
  521. Kristoffer Pons Bertelsen, 2022. "The Prior Adaptive Group Lasso and the Factor Zoo," CREATES Research Papers 2022-05, Department of Economics and Business Economics, Aarhus University.
  522. Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
  523. Armin Rauschenberger & Iuliana Ciocănea-Teodorescu & Marianne A. Jonker & Renée X. Menezes & Mark A. Wiel, 2020. "Sparse classification with paired covariates," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(3), pages 571-588, September.
  524. Daeju Kim & Shuichi Kawano & Yoshiyuki Ninomiya, 2014. "Adaptive basis expansion via $$\ell _1$$ ℓ 1 trend filtering," Computational Statistics, Springer, vol. 29(5), pages 1005-1023, October.
  525. Chakraborty, Sounak, 2009. "Bayesian binary kernel probit model for microarray based cancer classification and gene selection," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4198-4209, October.
  526. Yan Li & Chun Yu & Yize Zhao & Weixin Yao & Robert H. Aseltine & Kun Chen, 2022. "Pursuing sources of heterogeneity in modeling clustered population," Biometrics, The International Biometric Society, vol. 78(2), pages 716-729, June.
  527. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
  528. Jiahan Li, 2015. "Sparse and Stable Portfolio Selection With Parameter Uncertainty," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 381-392, July.
  529. Liang, Chao & Xu, Yongan & Wang, Jianqiong & Yang, Mo, 2022. "Whether dimensionality reduction techniques can improve the ability of sentiment proxies to predict stock market returns," International Review of Financial Analysis, Elsevier, vol. 82(C).
  530. Zhigang Li & Katherine Lee & Margaret R. Karagas & Juliette C. Madan & Anne G. Hoen & A. James O’Malley & Hongzhe Li, 2018. "Conditional Regression Based on a Multivariate Zero-Inflated Logistic-Normal Model for Microbiome Relative Abundance Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(3), pages 587-608, December.
  531. Salisu, Afees A. & Tchankam, Jean Paul, 2022. "US Stock return predictability with high dimensional models," Finance Research Letters, Elsevier, vol. 45(C).
  532. Hua Yun Chen & Hesen Li & Maria Argos & Victoria W. Persky & Mary E. Turyk, 2022. "Statistical Methods for Assessing the Explained Variation of a Health Outcome by a Mixture of Exposures," IJERPH, MDPI, vol. 19(5), pages 1-16, February.
  533. Edoardo Pasolli & Duy Tin Truong & Faizan Malik & Levi Waldron & Nicola Segata, 2016. "Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights," PLOS Computational Biology, Public Library of Science, vol. 12(7), pages 1-26, July.
  534. Kazim Topuz & Hasmet Uner & Asil Oztekin & Mehmet Bayram Yildirim, 2018. "Predicting pediatric clinic no-shows: a decision analytic framework using elastic net and Bayesian belief network," Annals of Operations Research, Springer, vol. 263(1), pages 479-499, April.
  535. Yen, Yu-Min & Yen, Tso-Jung, 2014. "Solving norm constrained portfolio optimization via coordinate-wise descent algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 737-759.
  536. Yumei Ren & Guoqiang Tang & Xin Li & Xuchang Chen, 2023. "A Study of Multifactor Quantitative Stock-Selection Strategies Incorporating Knockoff and Elastic Net-Logistic Regression," Mathematics, MDPI, vol. 11(16), pages 1-20, August.
  537. Lu, Xinjie & Ma, Feng & Xu, Jin & Zhang, Zehui, 2022. "Oil futures volatility predictability: New evidence based on machine learning models11All the authors contribute to the paper equally," International Review of Financial Analysis, Elsevier, vol. 83(C).
  538. Feng‐Chang Lin & Quefeng Li & Jessica T. Lin, 2020. "Relapse or reinfection: Classification of malaria infection using transition likelihoods," Biometrics, The International Biometric Society, vol. 76(4), pages 1351-1363, December.
  539. Zanin, Luca, 2020. "Combining multiple probability predictions in the presence of class imbalance to discriminate between potential bad and good borrowers in the peer-to-peer lending market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
  540. Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian nonparametric sparse seemingly unrelated regression model (SUR)," Working Papers 2016:20, Department of Economics, University of Venice "Ca' Foscari".
  541. Huang, Lele & Zhao, Junlong & Wang, Huiwen & Wang, Siyang, 2016. "Robust shrinkage estimation and selection for functional multiple linear model through LAD loss," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 384-400.
  542. Gilles Celeux & Mohammed El Anbari & Jean-Michel Marin & Christian P. Robert, 2010. "Regularization in Regression : Comparing Bayesian and Frequentist Methods in a Poorly Informative Situation," Working Papers 2010-43, Center for Research in Economics and Statistics.
  543. Gao Wang & Abhishek Sarkar & Peter Carbonetto & Matthew Stephens, 2020. "A simple new approach to variable selection in regression, with application to genetic fine mapping," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(5), pages 1273-1300, December.
  544. Jing Qian & Seyedmehdi Payabvash & André Kemmling & Michael H. Lev & Lee H. Schwamm & Rebecca A. Betensky, 2014. "Variable selection and prediction using a nested, matched case-control study: Application to hospital acquired pneumonia in stroke patients," Biometrics, The International Biometric Society, vol. 70(1), pages 153-163, March.
  545. Michail Filippidis & George Filis & Georgios Magkonis & Panagiotis Tzouvanas, 2023. "Evaluating robust determinants of the WTI/Brent oil price differential: A dynamic model averaging analysis," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 807-825, June.
  546. Saxena, Harshit & Aponte, Omar & McConky, Katie T., 2019. "A hybrid machine learning model for forecasting a billing period’s peak electric load days," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1288-1303.
  547. Wang, Jianqiu & Wu, Ke & Tong, Guoshi & Chen, Dongxu, 2023. "Nonlinearity in the cross-section of stock returns: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 174-205.
  548. Thomas Despois & Catherine Doz, 2022. "Identifying and interpreting the factors in factor models via sparsity : Different approaches," Working Papers halshs-03626503, HAL.
  549. Zhao, Shaofei & Fu, Guifang, 2022. "Distribution-free and model-free multivariate feature screening via multivariate rank distance correlation," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
  550. Feng Hong & Lu Tian & Viswanath Devanarayan, 2023. "Improving the Robustness of Variable Selection and Predictive Performance of Regularized Generalized Linear Models and Cox Proportional Hazard Models," Mathematics, MDPI, vol. 11(3), pages 1-13, January.
  551. Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023. "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, vol. 64(C).
  552. Min Chen & Yimin Lian & Zhao Chen & Zhengjun Zhang, 2017. "Sure explained variability and independence screening," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(4), pages 849-883, October.
  553. Shutes, Karl & Adcock, Chris, 2013. "Regularized Extended Skew-Normal Regression," MPRA Paper 58445, University Library of Munich, Germany, revised 09 Sep 2014.
  554. Fabio Caccioli & Imre Kondor & Matteo Marsili & Susanne Still, 2016. "Liquidity Risk And Instabilities In Portfolio Optimization," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(05), pages 1-28, August.
  555. Wenning Feng & Abdhi Sarkar & Chae Young Lim & Tapabrata Maiti, 2016. "Variable selection for binary spatial regression: Penalized quasi‐likelihood approach," Biometrics, The International Biometric Society, vol. 72(4), pages 1164-1172, December.
  556. Daniel, Jeffrey & Horrocks, Julie & Umphrey, Gary J., 2018. "Penalized composite likelihoods for inhomogeneous Gibbs point process models," Computational Statistics & Data Analysis, Elsevier, vol. 124(C), pages 104-116.
  557. Xiaoqiao Wang & Jian Miao & Tianpeng Chang & Jiangwei Xia & Binxin An & Yan Li & Lingyang Xu & Lupei Zhang & Xue Gao & Junya Li & Huijiang Gao, 2019. "Evaluation of GBLUP, BayesB and elastic net for genomic prediction in Chinese Simmental beef cattle," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-14, February.
  558. Blazquez, Desamparados & Domenech, Josep, 2018. "Big Data sources and methods for social and economic analyses," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 99-113.
  559. Sara Cecchetti, 2020. "An analysis of sovereign credit risk premia in the euro area: are they explained by local or global factors?," Temi di discussione (Economic working papers) 1271, Bank of Italy, Economic Research and International Relations Area.
  560. Boriss Siliverstovs, 2017. "Short-term forecasting with mixed-frequency data: a MIDASSO approach," Applied Economics, Taylor & Francis Journals, vol. 49(13), pages 1326-1343, March.
  561. Wang, Shixuan & Syntetos, Aris A. & Liu, Ying & Di Cairano-Gilfedder, Carla & Naim, Mohamed M., 2023. "Improving automotive garage operations by categorical forecasts using a large number of variables," European Journal of Operational Research, Elsevier, vol. 306(2), pages 893-908.
  562. Mehmet Caner & Anders Bredahl Kock, 2016. "Oracle Inequalities for Convex Loss Functions with Nonlinear Targets," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1377-1411, December.
  563. Yang, Yanlin & Hu, Xuemei & Jiang, Huifeng, 2022. "Group penalized logistic regressions predict up and down trends for stock prices," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
  564. Sarkar, Mainak & De Bruyn, Arnaud, 2021. "LSTM Response Models for Direct Marketing Analytics: Replacing Feature Engineering with Deep Learning," Journal of Interactive Marketing, Elsevier, vol. 53(C), pages 80-95.
  565. Jaehyuk Choi & Desheng Ge & Kyu Ho Kang & Sungbin Sohn, 2021. "Yield Spread Selection in Predicting Recession Probabilities: A Machine Learning Approach," Papers 2101.09394, arXiv.org, revised Jan 2022.
  566. Matteo Barigozzi & Marc Hallin, 2017. "A network analysis of the volatility of high dimensional financial series," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(3), pages 581-605, April.
  567. Maiorova, Ksenia & Fokin, Nikita, 2020. "Наукастинг Темпов Роста Стоимостных Объемов Экспорта И Импорта По Товарным Группам [Nowcasting the growth rates of the export and import by commodity groups]," MPRA Paper 109557, University Library of Munich, Germany.
  568. Etay Hay & Petra Ritter & Nancy J Lobaugh & Anthony R McIntosh, 2017. "Multiregional integration in the brain during resting-state fMRI activity," PLOS Computational Biology, Public Library of Science, vol. 13(3), pages 1-20, March.
  569. Wei Pan & Benhuai Xie & Xiaotong Shen, 2010. "Incorporating Predictor Network in Penalized Regression with Application to Microarray Data," Biometrics, The International Biometric Society, vol. 66(2), pages 474-484, June.
  570. Zhoubing Xu & Andrew J Asman & Rebeccah B Baucom & Richard G Abramson & Benjamin K Poulose & Bennett A Landman, 2015. "Quantitative CT Imaging of Ventral Hernias: Preliminary Validation of an Anatomical Labeling Protocol," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-17, October.
  571. Taha Alshaybawee & Habshah Midi & Rahim Alhamzawi, 2017. "Bayesian elastic net single index quantile regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(5), pages 853-871, April.
  572. Li, Kai & Ma, Minda & Xiang, Xiwang & Feng, Wei & Ma, Zhili & Cai, Weiguang & Ma, Xin, 2022. "Carbon reduction in commercial building operations: A provincial retrospection in China," Applied Energy, Elsevier, vol. 306(PB).
  573. Jiang, Minqi & Liu, Jiapeng & Zhang, Lu, 2021. "An extended regularized Kalman filter based on Genetic Algorithm: Application to dynamic asset pricing models," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 28-44.
  574. Jiang, He & Luo, Shihua & Dong, Yao, 2021. "Simultaneous feature selection and clustering based on square root optimization," European Journal of Operational Research, Elsevier, vol. 289(1), pages 214-231.
  575. Gurgul Henryk & Machno Artur, 2017. "Trade Pattern on Warsaw Stock Exchange and Prediction of Number of Trades," Statistics in Transition New Series, Polish Statistical Association, vol. 18(1), pages 91-114, March.
  576. Chen, Ya & Tsionas, Mike G. & Zelenyuk, Valentin, 2021. "LASSO+DEA for small and big wide data," Omega, Elsevier, vol. 102(C).
  577. Silvia Peracchi, 2022. "The Migration Crisis in the Local News: Evidence from the French-Italian Border," CESifo Working Paper Series 10070, CESifo.
  578. Guerra Urzola, Rosember & Van Deun, Katrijn & Vera, J. C. & Sijtsma, K., 2021. "A guide for sparse PCA : Model comparison and applications," Other publications TiSEM 4d35b931-7f49-444b-b92f-a, Tilburg University, School of Economics and Management.
  579. Mandal, B.N. & Ma, Jun, 2016. "l1 regularized multiplicative iterative path algorithm for non-negative generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 289-299.
  580. Alec Smith & B. Douglas Bernheim & Colin F. Camerer & Antonio Rangel, 2014. "Neural Activity Reveals Preferences without Choices," American Economic Journal: Microeconomics, American Economic Association, vol. 6(2), pages 1-36, May.
  581. Tino Werner, 2022. "Asymptotic linear expansion of regularized M-estimators," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(1), pages 167-194, February.
  582. Chen Xu & Jiahua Chen, 2014. "The Sparse MLE for Ultrahigh-Dimensional Feature Screening," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1257-1269, September.
  583. Xiaojun Mao & Zhonglei Wang & Shu Yang, 2023. "Matrix completion under complex survey sampling," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(3), pages 463-492, June.
  584. Joyee Ghosh & Andrew E. Ghattas, 2015. "Bayesian Variable Selection Under Collinearity," The American Statistician, Taylor & Francis Journals, vol. 69(3), pages 165-173, August.
  585. Elena Ivona DUMITRESCU & Sullivan HUE & Christophe HURLIN & Sessi TOKPAVI, 2020. "Machine Learning or Econometrics for Credit Scoring: Let’s Get the Best of Both Worlds," LEO Working Papers / DR LEO 2839, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  586. Garvit Arora & Shubhangi Tiwari & Ying Wu & Xuan Mei, 2024. "An Exploration to the Correlation Structure and Clustering of Macroeconomic Variables," Papers 2401.10162, arXiv.org, revised Jan 2024.
  587. de Bondt, Gabe J. & Hahn, Elke & Zekaite, Zivile, 2021. "ALICE: Composite leading indicators for euro area inflation cycles," International Journal of Forecasting, Elsevier, vol. 37(2), pages 687-707.
  588. Beckmann, Joscha & Schüssler, Rainer, 2016. "Forecasting exchange rates under parameter and model uncertainty," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 267-288.
  589. Kubus Mariusz, 2020. "The Influence of Unbalanced Economic Data on Feature Selection and Quality of Classifiers," Folia Oeconomica Stetinensia, Sciendo, vol. 20(1), pages 232-247, June.
  590. Kapetanios, George & Zikes, Filip, 2018. "Time-varying Lasso," Economics Letters, Elsevier, vol. 169(C), pages 1-6.
  591. Takumi Saegusa & Tianzhou Ma & Gang Li & Ying Qing Chen & Mei-Ling Ting Lee, 2020. "Variable Selection in Threshold Regression Model with Applications to HIV Drug Adherence Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(3), pages 376-398, December.
  592. Zhiyong Huang & Ziyan Luo & Naihua Xiu, 2019. "High-Dimensional Least-Squares with Perfect Positive Correlation," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(04), pages 1-16, August.
  593. Dimitris Korobilis, 2018. "Machine Learning Macroeconometrics: A Primer," Working Paper series 18-30, Rimini Centre for Economic Analysis.
  594. Ma, Feng & Lu, Xinjie & Liu, Jia & Huang, Dengshi, 2022. "Macroeconomic attention and stock market return predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
  595. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Annals of Economics and Statistics, GENES, issue 123-124, pages 333-361.
  596. Barzin,Samira & Avner,Paolo & Maruyama Rentschler,Jun Erik & O’Clery,Neave, 2022. "Where Are All the Jobs ? A Machine Learning Approach for High Resolution Urban Employment Prediction inDeveloping Countries," Policy Research Working Paper Series 9979, The World Bank.
  597. Paolo Fornaro & Henri Luomaranta, 2020. "Nowcasting Finnish real economic activity: a machine learning approach," Empirical Economics, Springer, vol. 58(1), pages 55-71, January.
  598. Lin, Hai & Tao, Xinyuan & Wu, Chunchi, 2022. "Forecasting earnings with combination of analyst forecasts," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 133-159.
  599. Pham Duy Khanh & Boris S. Mordukhovich & Vo Thanh Phat & Dat Ba Tran, 2023. "Generalized damped Newton algorithms in nonsmooth optimization via second-order subdifferentials," Journal of Global Optimization, Springer, vol. 86(1), pages 93-122, May.
  600. Li, Gaorong & Lian, Heng & Feng, Sanying & Zhu, Lixing, 2013. "Automatic variable selection for longitudinal generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 174-186.
  601. Pedro I. Hancevic & Hector H. Sandoval, 2023. "Solar Panel Adoption in SMEs in Emerging Countries," Working Papers 222, Red Nacional de Investigadores en Economía (RedNIE).
  602. Amir Beck & Yakov Vaisbourd, 2016. "The Sparse Principal Component Analysis Problem: Optimality Conditions and Algorithms," Journal of Optimization Theory and Applications, Springer, vol. 170(1), pages 119-143, July.
  603. Stadtmüller, Immo & Auer, Benjamin R. & Schuhmacher, Frank, 2022. "On the benefits of active stock selection strategies for diversified investors," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 342-354.
  604. Herrera, Gabriel Paes & Constantino, Michel & Su, Jen-Je & Naranpanawa, Athula, 2023. "The use of ICTs and income distribution in Brazil: A machine learning explanation using SHAP values," Telecommunications Policy, Elsevier, vol. 47(8).
  605. International Monetary Fund, 2016. "United Kingdom: Financial Sector Assessment Program-Systemic Risk and Interconnectedness Analysis-Technical Note," IMF Staff Country Reports 2016/164, International Monetary Fund.
  606. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.
  607. Mansoor Sheikh & A. C. C. Coolen, 2020. "Accurate Bayesian Data Classification Without Hyperparameter Cross-Validation," Journal of Classification, Springer;The Classification Society, vol. 37(2), pages 277-297, July.
  608. Thomas Despois & Catherine Doz, 2022. "Identifying and interpreting the factors in factor models via sparsity : Different approaches," PSE Working Papers halshs-03626503, HAL.
  609. Stephanie Houle & Ryan Macdonald, 2023. "Identifying Nascent High-Growth Firms Using Machine Learning," Staff Working Papers 23-53, Bank of Canada.
  610. Zeng, Yaohui & Yang, Tianbao & Breheny, Patrick, 2021. "Hybrid safe–strong rules for efficient optimization in lasso-type problems," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
  611. W. Holmes Finch, 2018. "Modeling High Dimensional Multilevel Data using the Lasso Estimator: A Simulation Study," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 7(1), pages 1-3.
  612. Tutz, Gerhard & Binder, Harald, 2007. "Boosting ridge regression," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6044-6059, August.
  613. Tamara, Novian & Dwi Muchisha, Nadya & Andriansyah, Andriansyah & Soleh, Agus M, 2020. "Nowcasting Indonesia’s GDP Growth Using Machine Learning Algorithms," MPRA Paper 105235, University Library of Munich, Germany.
  614. Kristoffer H. Hellton, 2023. "Penalized angular regression for personalized predictions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 184-212, March.
  615. Zemin Zheng & Jie Zhang & Yang Li, 2022. "L 0 -Regularized Learning for High-Dimensional Additive Hazards Regression," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2762-2775, September.
  616. Roberts, S. & Nowak, G., 2014. "Stabilizing the lasso against cross-validation variability," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 198-211.
  617. Xiao, Zhen & Zhang, Qi, 2022. "Dimension reduction for block-missing data based on sparse sliced inverse regression," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
  618. Tian, Tian Siva & James, Gareth M., 2013. "Interpretable dimension reduction for classifying functional data," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 282-296.
  619. Jiqian Wang & Feng Ma & Elie Bouri & Yangli Guo, 2023. "Which factors drive Bitcoin volatility: Macroeconomic, technical, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 970-988, July.
  620. Du, Yu & Lin, Xiaodong & Pham, Minh & Ruszczyński, Andrzej, 2021. "Selective linearization for multi-block statistical learning," European Journal of Operational Research, Elsevier, vol. 293(1), pages 219-228.
  621. Rong Liu & Shishun Zhao & Tao Hu & Jianguo Sun, 2022. "Variable Selection for Generalized Linear Models with Interval-Censored Failure Time Data," Mathematics, MDPI, vol. 10(5), pages 1-18, February.
  622. Yi Zhao & Bingkai Wang & Chin‐Fu Liu & Andreia V. Faria & Michael I. Miller & Brian S. Caffo & Xi Luo, 2023. "Identifying brain hierarchical structures associated with Alzheimer's disease using a regularized regression method with tree predictors," Biometrics, The International Biometric Society, vol. 79(3), pages 2333-2345, September.
  623. Thomas Despois & Catherine Doz, 2023. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 533-555, June.
  624. Charles Bouveyron & Camille Brunet-Saumard, 2014. "Discriminative variable selection for clustering with the sparse Fisher-EM algorithm," Computational Statistics, Springer, vol. 29(3), pages 489-513, June.
  625. Orianna DeMasi & Konrad Kording & Benjamin Recht, 2017. "Meaningless comparisons lead to false optimism in medical machine learning," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-15, September.
  626. Shan Huang & Chen Wang & Yuan Yuan & Jinglong Zhao & Jingjing Zhang, 2023. "Estimating Effects of Long-Term Treatments," Papers 2308.08152, arXiv.org.
  627. Hanmer,Lucia C. & Rubiano Matulevich,Eliana Carolina & Santamaria,Julieth, 2021. "Differences in Household Composition : Hidden Dimensions of Poverty and Displacement in Somalia," Policy Research Working Paper Series 9818, The World Bank.
  628. Li, Xin & Wu, Dongya & Li, Chong & Wang, Jinhua & Yao, Jen-Chih, 2020. "Sparse recovery via nonconvex regularized M-estimators over ℓq-balls," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
  629. Zhigeng Geng & Sijian Wang & Menggang Yu & Patrick O. Monahan & Victoria Champion & Grace Wahba, 2015. "Group variable selection via convex log-exp-sum penalty with application to a breast cancer survivor study," Biometrics, The International Biometric Society, vol. 71(1), pages 53-62, March.
  630. Fei Liu & David Dunson & Fei Zou, 2011. "High-Dimensional Variable Selection in Meta-Analysis for Censored Data," Biometrics, The International Biometric Society, vol. 67(2), pages 504-512, June.
  631. Korobilis, Dimitris, 2013. "Hierarchical shrinkage priors for dynamic regressions with many predictors," International Journal of Forecasting, Elsevier, vol. 29(1), pages 43-59.
  632. Nima Ezami & Aybike Özyüksel Çiftçioğlu & Masoomeh Mirrashid & Hosein Naderpour, 2023. "Advancing Shear Capacity Estimation in Rectangular RC Beams: A Cutting-Edge Artificial Intelligence Approach for Assessing the Contribution of FRP," Sustainability, MDPI, vol. 15(22), pages 1-25, November.
  633. Marijn A. Bolhuis & Swapnika R. Rachapalli & Diego Restuccia, 2021. "Misallocation in Indian Agriculture," NBER Working Papers 29363, National Bureau of Economic Research, Inc.
  634. Ueki, Masao, 2021. "Testing conditional mean through regression model sequence using Yanai’s generalized coefficient of determination," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
  635. Peng Zeng & Qinqin Hu & Xiaoyu Li, 2017. "Geometry and Degrees of Freedom of Linearly Constrained Generalized Lasso," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 989-1008, December.
  636. Szefer Elena & Graham Jinko & Lu Donghuan & Beg Mirza Faisal & Nathoo Farouk, 2017. "Multivariate association between single-nucleotide polymorphisms in Alzgene linkage regions and structural changes in the brain: discovery, refinement and validation," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(5-6), pages 349-365, December.
  637. Yichao Wu, 2011. "An ordinary differential equation-based solution path algorithm," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(1), pages 185-199.
  638. Brendan P. W. Ames & Mingyi Hong, 2016. "Alternating direction method of multipliers for penalized zero-variance discriminant analysis," Computational Optimization and Applications, Springer, vol. 64(3), pages 725-754, July.
  639. Wang, Jia & Cai, Xizhen & Li, Runze, 2021. "Variable selection for partially linear models via Bayesian subset modeling with diffusing prior," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
  640. Gilles Charmet & Louis-Gautier Tran & Jérôme Auzanneau & Renaud Rincent & Sophie Bouchet, 2020. "BWGS: A R package for genomic selection and its application to a wheat breeding programme," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-20, April.
  641. Sahoko Furuta & Yudai Hatayama & Atsushi Kawakami & Yusuke Oh, 2021. "New Hedonic Quality Adjustment Method using Sparse Estimation," Bank of Japan Working Paper Series 21-E-8, Bank of Japan.
  642. Ghaddar, Bissan & Naoum-Sawaya, Joe, 2018. "High dimensional data classification and feature selection using support vector machines," European Journal of Operational Research, Elsevier, vol. 265(3), pages 993-1004.
  643. Xi Dong & Yan Li & David E. Rapach & Guofu Zhou, 2022. "Anomalies and the Expected Market Return," Journal of Finance, American Finance Association, vol. 77(1), pages 639-681, February.
  644. Umberto Amato & Anestis Antoniadis & Italia De Feis & Irene Gijbels, 2021. "Penalised robust estimators for sparse and high-dimensional linear models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 1-48, March.
  645. Lee, Kuo-Jung & Feldkircher, Martin & Chen, Yi-Chi, 2021. "Variable selection in finite mixture of regression models with an unknown number of components," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
  646. Ahn, Yongkil & Tsai, Shih-Chuan, 2021. "What factors are associated with stock price jumps in high frequency?," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
  647. Feihong Xia & Rabikar Chatterjee & Jerrold H. May, 2019. "Using Conditional Restricted Boltzmann Machines to Model Complex Consumer Shopping Patterns," Marketing Science, INFORMS, vol. 38(4), pages 711-727, July.
  648. Augusto Destrero & Sofia Mosci & Christine Mol & Alessandro Verri & Francesca Odone, 2009. "Feature selection for high-dimensional data," Computational Management Science, Springer, vol. 6(1), pages 25-40, February.
  649. Vrontos, Spyridon D. & Galakis, John & Vrontos, Ioannis D., 2021. "Modeling and predicting U.S. recessions using machine learning techniques," International Journal of Forecasting, Elsevier, vol. 37(2), pages 647-671.
  650. Thangjam, Aditya & Jaipuria, Sanjita & Dadabada, Pradeep Kumar, 2023. "Time-Varying approaches for Long-Term Electric Load Forecasting under economic shocks," Applied Energy, Elsevier, vol. 333(C).
  651. Fakhri J. Hasanov & Muhammad Javid & Frederick L. Joutz, 2022. "Saudi Non-Oil Exports before and after COVID-19: Historical Impacts of Determinants and Scenario Analysis," Sustainability, MDPI, vol. 14(4), pages 1-38, February.
  652. Lee Kyu Ha & Chakraborty Sounak & Sun Jianguo, 2011. "Bayesian Variable Selection in Semiparametric Proportional Hazards Model for High Dimensional Survival Data," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-32, April.
  653. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2023. "Gold risk premium estimation with machine learning methods," Journal of Commodity Markets, Elsevier, vol. 31(C).
  654. Bedoui, Adel & Lazar, Nicole A., 2020. "Bayesian empirical likelihood for ridge and lasso regressions," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).
  655. Devriendt, Sander & Antonio, Katrien & Reynkens, Tom & Verbelen, Roel, 2021. "Sparse regression with Multi-type Regularized Feature modeling," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 248-261.
  656. Merten, Michael & Rücker, Fabian & Schoeneberger, Ilka & Sauer, Dirk Uwe, 2020. "Automatic frequency restoration reserve market prediction: Methodology and comparison of various approaches," Applied Energy, Elsevier, vol. 268(C).
  657. Rossini, Jacopo & Canale, Antonio, 2019. "Quantifying prediction uncertainty for functional-and-scalar to functional autoregressive models under shape constraints," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 221-231.
  658. Peter Martey Addo & Dominique Guegan & Bertrand Hassani, 2018. "Credit Risk Analysis using Machine and Deep Learning models," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01719983, HAL.
  659. Rosato, Antonello & Panella, Massimo & Andreotti, Amedeo & Mohammed, Osama A. & Araneo, Rodolfo, 2021. "Two-stage dynamic management in energy communities using a decision system based on elastic net regularization," Applied Energy, Elsevier, vol. 291(C).
  660. Anindya Bhadra & Jyotishka Datta & Nicholas G. Polson & Brandon T. Willard, 2021. "The Horseshoe-Like Regularization for Feature Subset Selection," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 185-214, May.
  661. Yu, Dengdeng & Zhang, Li & Mizera, Ivan & Jiang, Bei & Kong, Linglong, 2019. "Sparse wavelet estimation in quantile regression with multiple functional predictors," Computational Statistics & Data Analysis, Elsevier, vol. 136(C), pages 12-29.
  662. Gelper, Sarah & Stremersch, Stefan, 2014. "Variable selection in international diffusion models," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 356-367.
  663. Antonis Christou & Andreas Artemiou, 2023. "Adaptive L0 Regularization for Sparse Support Vector Regression," Mathematics, MDPI, vol. 11(13), pages 1-12, June.
  664. Andrzej Wójtowicz & Jan Piekarczyk & Marek Wójtowicz & Jarosław Jasiewicz & Sławomir Królewicz & Elżbieta Starzycka-Korbas, 2023. "Classification of Plenodomus lingam and Plenodomus biglobosus in Co-Occurring Samples Using Reflectance Spectroscopy," Agriculture, MDPI, vol. 13(12), pages 1-14, November.
  665. Samuel P Leighton & Rajeev Krishnadas & Kelly Chung & Alison Blair & Susie Brown & Suzy Clark & Kathryn Sowerbutts & Matthias Schwannauer & Jonathan Cavanagh & Andrew I Gumley, 2019. "Predicting one-year outcome in first episode psychosis using machine learning," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-14, March.
  666. Michael Funke & Kadri Männasoo & Helery Tasane, 2023. "Regional Economic Impacts of the Øresund Cross-Border Fixed Link: Cui Bono?," CESifo Working Paper Series 10557, CESifo.
  667. Bloise, Francesco & Tancioni, Massimiliano, 2021. "Predicting the spread of COVID-19 in Italy using machine learning: Do socio-economic factors matter?," Structural Change and Economic Dynamics, Elsevier, vol. 56(C), pages 310-329.
  668. Ruth M. Pfeiffer & Andrew Redd & Raymond J. Carroll, 2017. "On the impact of model selection on predictor identification and parameter inference," Computational Statistics, Springer, vol. 32(2), pages 667-690, June.
  669. Bahadır Yüzbaşı & Mohammad Arashi & S. Ejaz Ahmed, 2020. "Shrinkage Estimation Strategies in Generalised Ridge Regression Models: Low/High‐Dimension Regime," International Statistical Review, International Statistical Institute, vol. 88(1), pages 229-251, April.
  670. Kepplinger, David, 2023. "Robust variable selection and estimation via adaptive elastic net S-estimators for linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 183(C).
  671. Xiao Ni & Daowen Zhang & Hao Helen Zhang, 2010. "Variable Selection for Semiparametric Mixed Models in Longitudinal Studies," Biometrics, The International Biometric Society, vol. 66(1), pages 79-88, March.
  672. Wei Tang & Steven L Bressler & Chad M Sylvester & Gordon L Shulman & Maurizio Corbetta, 2012. "Measuring Granger Causality between Cortical Regions from Voxelwise fMRI BOLD Signals with LASSO," PLOS Computational Biology, Public Library of Science, vol. 8(5), pages 1-14, May.
  673. Schäfer, Christian, 2012. "Monte Carlo methods for sampling high-dimensional binary vectors," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/10860 edited by Chopin, Nicolas.
  674. Guillaume Belly & Lukas Boeckelmann & Carlos Mateo Caicedo Graciano & Alberto Di Iorio & Klodiana Istrefi & Vasileios Siakoulis & Arthur Stalla‐Bourdillon, 2023. "Forecasting sovereign risk in the Euro area via machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 657-684, April.
  675. Guangrui Tang & Neng Fan, 2022. "A Survey of Solution Path Algorithms for Regression and Classification Models," Annals of Data Science, Springer, vol. 9(4), pages 749-789, August.
  676. Yagli, Gokhan Mert & Yang, Dazhi & Srinivasan, Dipti, 2019. "Automatic hourly solar forecasting using machine learning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 487-498.
  677. Raymond C. W. Leung & Yu-Man Tam, 2021. "Statistical Arbitrage Risk Premium by Machine Learning," Papers 2103.09987, arXiv.org.
  678. Thomas D Stuckey & Roger S Gammon & Robi Goswami & Jeremiah P Depta & John A Steuter & Frederick J Meine III & Michael C Roberts & Narendra Singh & Shyam Ramchandani & Tim Burton & Paul Grouchy & Ali , 2018. "Cardiac Phase Space Tomography: A novel method of assessing coronary artery disease utilizing machine learning," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-12, August.
  679. Ruidi Chen & Ioannis Ch. Paschalidis, 2022. "Robust Grouped Variable Selection Using Distributionally Robust Optimization," Journal of Optimization Theory and Applications, Springer, vol. 194(3), pages 1042-1071, September.
  680. Jhong, Jae-Hwan & Koo, Ja-Yong, 2019. "Simultaneous estimation of quantile regression functions using B-splines and total variation penalty," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 228-244.
  681. Juan C. Laria & M. Carmen Aguilera-Morillo & Rosa E. Lillo, 2023. "Group linear algorithm with sparse principal decomposition: a variable selection and clustering method for generalized linear models," Statistical Papers, Springer, vol. 64(1), pages 227-253, February.
  682. Sandra Stankiewicz, 2015. "Forecasting Euro Area Macroeconomic Variables with Bayesian Adaptive Elastic Net," Working Paper Series of the Department of Economics, University of Konstanz 2015-12, Department of Economics, University of Konstanz.
  683. Faisal Maqbool Zahid & Shahla Faisal & Christian Heumann, 2020. "Variable selection techniques after multiple imputation in high-dimensional data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(3), pages 553-580, September.
  684. Saad Haider & Raziur Rahman & Souparno Ghosh & Ranadip Pal, 2015. "A Copula Based Approach for Design of Multivariate Random Forests for Drug Sensitivity Prediction," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-22, December.
  685. Narayan, Seema & Smyth, Russell, 2015. "The financial econometrics of price discovery and predictability," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 380-393.
  686. Xiaofei Wu & Rongmei Liang & Hu Yang, 2022. "Penalized and constrained LAD estimation in fixed and high dimension," Statistical Papers, Springer, vol. 63(1), pages 53-95, February.
  687. Kai Carstensen & Felix Kießner & Thies Rossian, 2023. "Estimation of the TFP Gap for the Largest Five EMU Countries," CESifo Working Paper Series 10245, CESifo.
  688. Halko, Marja-Liisa & Lappalainen, Olli & Sääksvuori, Lauri, 2021. "Do non-choice data reveal economic preferences? Evidence from biometric data and compensation-scheme choice," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 87-104.
  689. Wenbo Wu & Jiaqi Chen & Liang Xu & Qingyun He & Michael L. Tindall, 2019. "A statistical learning approach for stock selection in the Chinese stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-18, December.
  690. Christoph F. Kurz & Martin Rehm & Rolf Holle & Christina Teuner & Michael Laxy & Larissa Schwarzkopf, 2019. "The effect of bariatric surgery on health care costs: A synthetic control approach using Bayesian structural time series," Health Economics, John Wiley & Sons, Ltd., vol. 28(11), pages 1293-1307, November.
  691. Oguzhan Cepni, Duc Khuong Nguyen, and Ahmet Sensoy, 2022. "News Media and Attention Spillover across Energy Markets: A Powerful Predictor of Crude Oil Futures Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
  692. Ying Wu & Richard J. Cook, 2015. "Penalized regression for interval‐censored times of disease progression: Selection of HLA markers in psoriatic arthritis," Biometrics, The International Biometric Society, vol. 71(3), pages 782-791, September.
  693. Andrew E. Clark & Conchita D'Ambrosio & Niccolo Gentile & Alexandre Tkatchenko, 2022. "What makes a satisfying life? Prediction and interpretation with machine-learning algorithms," CEP Discussion Papers dp1853, Centre for Economic Performance, LSE.
  694. Dennis Kant & Andreas Pick & Jasper de Winter, 2022. "Nowcasting GDP using machine learning methods," Working Papers 754, DNB.
  695. McCann, Lauren & Welsch, Roy E., 2007. "Robust variable selection using least angle regression and elemental set sampling," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 249-257, September.
  696. Henri Bonnel & Christopher Schneider, 2019. "Post-Pareto Analysis and a New Algorithm for the Optimal Parameter Tuning of the Elastic Net," Journal of Optimization Theory and Applications, Springer, vol. 183(3), pages 993-1027, December.
  697. Suriyan Jomthanachai & Wai Peng Wong & Khai Wah Khaw, 2024. "An Application of Machine Learning to Logistics Performance Prediction: An Economics Attribute-Based of Collective Instance," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 741-792, February.
  698. Nicholas Beauchamp, 2017. "Predicting and Interpolating State‐Level Polls Using Twitter Textual Data," American Journal of Political Science, John Wiley & Sons, vol. 61(2), pages 490-503, April.
  699. Qi Chen & Yanli Zhang-James & Eric J Barnett & Paul Lichtenstein & Jussi Jokinen & Brian M D’Onofrio & Stephen V Faraone & Henrik Larsson & Seena Fazel, 2020. "Predicting suicide attempt or suicide death following a visit to psychiatric specialty care: A machine learning study using Swedish national registry data," PLOS Medicine, Public Library of Science, vol. 17(11), pages 1-19, November.
  700. James Chapman & Ajit Desai, 2021. "Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19," Staff Working Papers 21-2, Bank of Canada.
  701. Quefeng Li & Sijian Wang & Chiang-Ching Huang & Menggang Yu & Jun Shao, 2014. "Meta-analysis based variable selection for gene expression data," Biometrics, The International Biometric Society, vol. 70(4), pages 872-880, December.
  702. Abbas Khalili & Shili Lin, 2013. "Regularization in Finite Mixture of Regression Models with Diverging Number of Parameters," Biometrics, The International Biometric Society, vol. 69(2), pages 436-446, June.
  703. Lingjing Jiang & Niina Haiminen & Anna‐Paola Carrieri & Shi Huang & Yoshiki Vázquez‐Baeza & Laxmi Parida & Ho‐Cheol Kim & Austin D. Swafford & Rob Knight & Loki Natarajan, 2022. "Utilizing stability criteria in choosing feature selection methods yields reproducible results in microbiome data," Biometrics, The International Biometric Society, vol. 78(3), pages 1155-1167, September.
  704. Lisa R. Goldberg & Saad Mouti, 2019. "Sustainable Investing and the Cross-Section of Returns and Maximum Drawdown," Papers 1905.05237, arXiv.org, revised Dec 2023.
  705. Blommaert, A. & Hens, N. & Beutels, Ph., 2014. "Data mining for longitudinal data under multicollinearity and time dependence using penalized generalized estimating equations," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 667-680.
  706. Cepni, Oguzhan & Güney, I. Ethem & Swanson, Norman R., 2019. "Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes," International Journal of Forecasting, Elsevier, vol. 35(2), pages 555-572.
  707. Stefan Kerbl & Michael Sigmund, 2011. "What Drives Aggregate Credit Risk?," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 22, pages 72-87.
  708. Orlando Anunciação & Susana Vinga & Arlindo L Oliveira, 2013. "Using Information Interaction to Discover Epistatic Effects in Complex Diseases," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-11, October.
  709. Margherita Giuzio & Sandra Paterlini, 2019. "Un-diversifying during crises: Is it a good idea?," Computational Management Science, Springer, vol. 16(3), pages 401-432, July.
  710. Xingcai Zhou & Yu Xiang, 2022. "ADMM-Based Differential Privacy Learning for Penalized Quantile Regression on Distributed Functional Data," Mathematics, MDPI, vol. 10(16), pages 1-28, August.
  711. Bergersen, Linn Cecilie & Tharmaratnam, Kukatharmini & Glad, Ingrid K., 2014. "Monotone splines lasso," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 336-351.
  712. Wang, Huiqiang, 2016. "Estimating the health impacts of food safety interventions: Optimal counterfactual selections via information criteria in small samples," Food Policy, Elsevier, vol. 63(C), pages 44-52.
  713. Maas, Benedikt, 2019. "Nowcasting and forecasting US recessions: Evidence from the Super Learner," MPRA Paper 96408, University Library of Munich, Germany.
  714. Yue, Mu & Li, Jialiang & Cheng, Ming-Yen, 2019. "Two-step sparse boosting for high-dimensional longitudinal data with varying coefficients," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 222-234.
  715. Mohammed A. A. Abulela & Amaniel P. Mrutu & Nasrah M. Ismail, 2023. "Learning and Study Strategies as Predictors of Undergraduates’ Emotional Engagement: A Cross-Validation Approach," SAGE Open, , vol. 13(1), pages 21582440231, February.
  716. Mishra, Aditya & Müller, Christian L., 2022. "Robust regression with compositional covariates," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).
  717. Mai Dao & Min Wang & Souparno Ghosh & Keying Ye, 2022. "Bayesian variable selection and estimation in quantile regression using a quantile-specific prior," Computational Statistics, Springer, vol. 37(3), pages 1339-1368, July.
  718. Bergersen Linn Cecilie & Glad Ingrid K. & Lyng Heidi, 2011. "Weighted Lasso with Data Integration," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-29, August.
  719. Xavier Bry & Ndèye Niang & Thomas Verron & Stéphanie Bougeard, 2023. "Clusterwise elastic-net regression based on a combined information criterion," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(1), pages 75-107, March.
  720. Seong-Yun Hong & Seonggook Moon & Sang-Hyun Chi & Yoon-Jae Cho & Jeon-Young Kang, 2022. "Local Sparse Principal Component Analysis for Exploring the Spatial Distribution of Social Infrastructure," Land, MDPI, vol. 11(11), pages 1-16, November.
  721. Ke Yu & Shan Luo, 2022. "A sequential feature selection procedure for high-dimensional Cox proportional hazards model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(6), pages 1109-1142, December.
  722. Charbonnier Camille & Chiquet Julien & Ambroise Christophe, 2010. "Weighted-LASSO for Structured Network Inference from Time Course Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-29, February.
  723. Camila Epprecht & Dominique Guegan & Álvaro Veiga & Joel Correa da Rosa, 2017. "Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics," Post-Print halshs-00917797, HAL.
  724. van Erp, Sara & Oberski, Daniel L. & Mulder, Joris, 2018. "Shrinkage priors for Bayesian penalized regression," OSF Preprints cg8fq, Center for Open Science.
  725. Guibert, Quentin & Lopez, Olivier & Piette, Pierrick, 2019. "Forecasting mortality rate improvements with a high-dimensional VAR," Insurance: Mathematics and Economics, Elsevier, vol. 88(C), pages 255-272.
  726. Li‐Pang Chen & Bangxu Qiu, 2023. "Analysis of length‐biased and partly interval‐censored survival data with mismeasured covariates," Biometrics, The International Biometric Society, vol. 79(4), pages 3929-3940, December.
  727. Vigo Pereira, Caio, 2021. "Portfolio efficiency with high-dimensional data as conditioning information," International Review of Financial Analysis, Elsevier, vol. 77(C).
  728. Fatemeh Tajik & Mingzheng Wang & Xiaohui Zhang & Jie Han, 2020. "Evaluation of the impact of body mass index on venous thromboembolism risk factors," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-17, July.
  729. Wang Zhu & Wang C.Y., 2010. "Buckley-James Boosting for Survival Analysis with High-Dimensional Biomarker Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-33, June.
  730. Felix Abramovich & Vadim Grinshtein, 2013. "Estimation of a sparse group of sparse vectors," Biometrika, Biometrika Trust, vol. 100(2), pages 355-370.
  731. Danhyang Lee & Jae Kwang Kim, 2022. "Semiparametric imputation using conditional Gaussian mixture models under item nonresponse," Biometrics, The International Biometric Society, vol. 78(1), pages 227-237, March.
  732. Peter Bühlmann, 2013. "Causal statistical inference in high dimensions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(3), pages 357-370, June.
  733. Wang, Zhengxin & Peng, Xinggan & Xia, Ao & Shah, Akeel A. & Yan, Huchao & Huang, Yun & Zhu, Xianqing & Zhu, Xun & Liao, Qiang, 2023. "Comparison of machine learning methods for predicting the methane production from anaerobic digestion of lignocellulosic biomass," Energy, Elsevier, vol. 263(PD).
  734. Wang, Mingqiu & Song, Lixin & Wang, Xiaoguang, 2010. "Bridge estimation for generalized linear models with a diverging number of parameters," Statistics & Probability Letters, Elsevier, vol. 80(21-22), pages 1584-1596, November.
  735. Luca Greco & Alessio Farcomeni, 2016. "A plug-in approach to sparse and robust principal component analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 449-481, September.
  736. Minh Pham & Xiaodong Lin & Andrzej Ruszczyński & Yu Du, 2021. "An outer–inner linearization method for non-convex and nondifferentiable composite regularization problems," Journal of Global Optimization, Springer, vol. 81(1), pages 179-202, September.
  737. Bai, Ray & Ghosh, Malay, 2018. "High-dimensional multivariate posterior consistency under global–local shrinkage priors," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 157-170.
  738. Jacobs, Jan P.A.M. & Otter, Pieter W. & den Reijer, Ard H.J., 2012. "Information, data dimension and factor structure," Journal of Multivariate Analysis, Elsevier, vol. 106(C), pages 80-91.
  739. Abdul Wahid & Dost Muhammad Khan & Ijaz Hussain, 2017. "Robust Adaptive Lasso method for parameter’s estimation and variable selection in high-dimensional sparse models," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-17, August.
  740. Howard D. Bondell & Brian J. Reich, 2008. "Simultaneous Regression Shrinkage, Variable Selection, and Supervised Clustering of Predictors with OSCAR," Biometrics, The International Biometric Society, vol. 64(1), pages 115-123, March.
  741. Kath, Christopher & Ziel, Florian, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Energy Economics, Elsevier, vol. 76(C), pages 411-423.
  742. Wei-Hsuan Lo-Ciganic & James L Huang & Hao H Zhang & Jeremy C Weiss & C Kent Kwoh & Julie M Donohue & Adam J Gordon & Gerald Cochran & Daniel C Malone & Courtney C Kuza & Walid F Gellad, 2020. "Using machine learning to predict risk of incident opioid use disorder among fee-for-service Medicare beneficiaries: A prognostic study," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-16, July.
  743. Runmin Wei & Jingye Wang & Erik Jia & Tianlu Chen & Yan Ni & Wei Jia, 2018. "GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-14, January.
  744. Peng Ye & Yong Li & Abu Bakkar Siddik, 2023. "Forecasting the Return of Carbon Price in the Chinese Market Based on an Improved Stacking Ensemble Algorithm," Energies, MDPI, vol. 16(11), pages 1-39, June.
  745. Gerhard Tutz & Moritz Berger, 2022. "Sparser Ordinal Regression Models Based on Parametric and Additive Location‐Shift Approaches," International Statistical Review, International Statistical Institute, vol. 90(2), pages 306-327, August.
  746. Haipeng Xing & Ying Chen, 2018. "Dependence of Structural Breaks in Rating Transition Dynamics on Economic and Market Variations," Review of Economics & Finance, Better Advances Press, Canada, vol. 11, pages 1-18, February.
  747. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
  748. Elliott Ash & Daniel L. Chen & Sergio Galletta, 2022. "Measuring Judicial Sentiment: Methods and Application to US Circuit Courts," Economica, London School of Economics and Political Science, vol. 89(354), pages 362-376, April.
  749. Nerea González-García & Ana Belén Nieto-Librero & Purificación Galindo-Villardón, 2023. "CenetBiplot: a new proposal of sparse and orthogonal biplots methods by means of elastic net CSVD," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(1), pages 5-19, March.
  750. Zhang, Bo & Chen, G.Q. & Xia, X.H. & Li, S.C. & Chen, Z.M. & Ji, Xi, 2012. "Environmental emissions by Chinese industry: Exergy-based unifying assessment," Energy Policy, Elsevier, vol. 45(C), pages 490-501.
  751. Geeven Geert & van der Laan Mark J. & de Gunst Mathisca C.M., 2012. "Comparison of Targeted Maximum Likelihood and Shrinkage Estimators of Parameters in Gene Networks," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(5), pages 1-29, September.
  752. Peter Bühlmann & Domagoj Ćevid, 2020. "Deconfounding and Causal Regularisation for Stability and External Validity," International Statistical Review, International Statistical Institute, vol. 88(S1), pages 114-134, December.
  753. Pierre Dodin & Jingyi Xiao & Yossiri Adulyasak & Neda Etebari Alamdari & Lea Gauthier & Philippe Grangier & Paul Lemaitre & William L. Hamilton, 2023. "Bombardier Aftermarket Demand Forecast with Machine Learning," Interfaces, INFORMS, vol. 53(6), pages 425-445, November.
  754. Xiaolu Wei & Hongbing Ouyang, 2023. "Forecasting Carbon Price Using Double Shrinkage Methods," IJERPH, MDPI, vol. 20(2), pages 1-20, January.
  755. Eliot Melissa & Ferguson Jane & Reilly Muredach P. & Foulkes Andrea S., 2011. "Ridge Regression for Longitudinal Biomarker Data," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-11, September.
  756. Lykou, Anastasia & Whittaker, Joe, 2010. "Sparse CCA using a Lasso with positivity constraints," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3144-3157, December.
  757. Seulki Chung, 2023. "Real-time Prediction of the Great Recession and the Covid-19 Recession," Papers 2310.08536, arXiv.org, revised Mar 2024.
  758. Jiang, Zhenzhen & Guo, Hongping & Wang, Jinjuan, 2023. "Feature screening for multiple responses," Journal of Multivariate Analysis, Elsevier, vol. 198(C).
  759. Alexis Comber & Khanh Chi & Man Q Huy & Quan Nguyen & Binbin Lu & Hoang H Phe & Paul Harris, 2020. "Distance metric choice can both reduce and induce collinearity in geographically weighted regression," Environment and Planning B, , vol. 47(3), pages 489-507, March.
  760. Rui Xu & Zonglei Zhen & Jia Liu, 2010. "Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-8, November.
  761. Jan Pablo Burgard & Joscha Krause & Ralf Münnich, 2019. "Penalized Small Area Models for the Combination of Unit- and Area-level Data," Research Papers in Economics 2019-05, University of Trier, Department of Economics.
  762. Ahn, Yongkil, 2022. "The anatomy of the disposition effect: Which factors are most important?," Finance Research Letters, Elsevier, vol. 44(C).
  763. Kyoungmi Hwang & Kyungsik Lee & Sungsoo Park, 2017. "Variable selection methods for multi-class classification using signomial function," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(9), pages 1117-1130, September.
  764. Shutes, Karl & Adcock, Chris, 2013. "Regularized Skew-Normal Regression," MPRA Paper 52217, University Library of Munich, Germany, revised 11 Dec 2013.
  765. Ma, Jun & Cheng, Jack C.P., 2016. "Estimation of the building energy use intensity in the urban scale by integrating GIS and big data technology," Applied Energy, Elsevier, vol. 183(C), pages 182-192.
  766. Robert Lehmann & Magnus Reif & Timo Wollmershäuser, 2020. "ifoCAST: The New Forecast Standard of the ifo Institute," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 73(11), pages 31-39, November.
  767. Autcha Araveeporn, 2021. "The Higher-Order of Adaptive Lasso and Elastic Net Methods for Classification on High Dimensional Data," Mathematics, MDPI, vol. 9(10), pages 1-14, May.
  768. JinXing Che & YouLong Yang, 2017. "Stochastic correlation coefficient ensembles for variable selection," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(10), pages 1721-1742, July.
  769. He Jiang, 2023. "Forecasting global solar radiation using a robust regularization approach with mixture kernels," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 1989-2010, December.
  770. Marius Arend & Yizhong Yuan & M. Águila Ruiz-Sola & Nooshin Omranian & Zoran Nikoloski & Dimitris Petroutsos, 2023. "Widening the landscape of transcriptional regulation of green algal photoprotection," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
  771. Tiziana Carpi & Airo Hino & Stefano Maria Iacus & Giuseppe Porro, 2021. "Twitter Subjective Well-Being Indicator During COVID-19 Pandemic: A Cross-Country Comparative Study," Papers 2101.07695, arXiv.org.
  772. Ploutarchos Tzampoglou & Dimitrios Loukidis, 2020. "Investigation of the Importance of Climatic Factors in COVID-19 Worldwide Intensity," IJERPH, MDPI, vol. 17(21), pages 1-25, October.
  773. Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019. "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, vol. 80(C), pages 423-433.
  774. Mai, Qing & Zou, Hui, 2015. "Sparse semiparametric discriminant analysis," Journal of Multivariate Analysis, Elsevier, vol. 135(C), pages 175-188.
  775. Anesti, Nikoleta & Kalamara, Eleni & Kapetanios, George, 2021. "Forecasting UK GDP growth with large survey panels," Bank of England working papers 923, Bank of England.
  776. Zichen Zhang & Ye Eun Bae & Jonathan R. Bradley & Lang Wu & Chong Wu, 2022. "SUMMIT: An integrative approach for better transcriptomic data imputation improves causal gene identification," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  777. Mariusz Kubus, 2016. "Locally Regularized Linear Regression In The Valuation Of Real Estate," Statistics in Transition New Series, Polish Statistical Association, vol. 17(3), pages 515-524, September.
  778. Hui Zhang & Yu-Hong Dai & Lei Guo & Wei Peng, 2021. "Proximal-Like Incremental Aggregated Gradient Method with Linear Convergence Under Bregman Distance Growth Conditions," Mathematics of Operations Research, INFORMS, vol. 46(1), pages 61-81, February.
  779. Maria-Carmen García-Centeno & Román Mínguez-Salido & Raúl del Pozo-Rubio, 2021. "The Classification of Profiles of Financial Catastrophe Caused by Out-of-Pocket Payments: A Methodological Approach," Mathematics, MDPI, vol. 9(11), pages 1-20, May.
  780. Iason Kynigakis & Ekaterini Panopoulou, 2022. "Does model complexity add value to asset allocation? Evidence from machine learning forecasting models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 603-639, April.
  781. Auer, Benjamin R. & Schuhmacher, Frank & Niemann, Sebastian, 2023. "Cloning mutual fund returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 31-37.
  782. Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019. "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 97-117.
  783. Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue forthcomi.
  784. Lian, Heng, 2012. "Shrinkage estimation for identification of linear components in additive models," Statistics & Probability Letters, Elsevier, vol. 82(2), pages 225-231.
  785. James Chapman & Ajit Desai, 2022. "Macroeconomic Predictions Using Payments Data and Machine Learning," Staff Working Papers 22-10, Bank of Canada.
  786. Nicholson, William B. & Matteson, David S. & Bien, Jacob, 2017. "VARX-L: Structured regularization for large vector autoregressions with exogenous variables," International Journal of Forecasting, Elsevier, vol. 33(3), pages 627-651.
  787. Bulut, Hasan, 2020. "The construction of a composite index for general satisfaction in Turkey and the investigation of its determinants," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
  788. Wang, Christina Dan & Chen, Zhao & Lian, Yimin & Chen, Min, 2022. "Asset selection based on high frequency Sharpe ratio," Journal of Econometrics, Elsevier, vol. 227(1), pages 168-188.
  789. Kozak, Serhiy & Nagel, Stefan & Santosh, Shrihari, 2020. "Shrinking the cross-section," Journal of Financial Economics, Elsevier, vol. 135(2), pages 271-292.
  790. Waidelich, Paul & Haug, Tomas & Wieshammer, Lorenz, 2022. "German efficiency gone wrong: Unintended incentives arising from the gas TSOs’ benchmarking," Energy Policy, Elsevier, vol. 160(C).
  791. Yang, Lu, 2023. "Oil price bubbles: The role of network centrality on idiosyncratic sovereign risk," Resources Policy, Elsevier, vol. 82(C).
  792. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
  793. Hsu, David, 2015. "Identifying key variables and interactions in statistical models of building energy consumption using regularization," Energy, Elsevier, vol. 83(C), pages 144-155.
  794. Miltiadis Iatrou & Christos Karydas & George Iatrou & Ioannis Pitsiorlas & Vassilis Aschonitis & Iason Raptis & Stelios Mpetas & Kostas Kravvas & Spiros Mourelatos, 2021. "Topdressing Nitrogen Demand Prediction in Rice Crop Using Machine Learning Systems," Agriculture, MDPI, vol. 11(4), pages 1-17, April.
  795. Benevento, Elisabetta & Aloini, Davide & Squicciarini, Nunzia, 2023. "Towards a real-time prediction of waiting times in emergency departments: A comparative analysis of machine learning techniques," International Journal of Forecasting, Elsevier, vol. 39(1), pages 192-208.
  796. Konrad Bogner & Florian Pappenberger & Massimiliano Zappa, 2019. "Machine Learning Techniques for Predicting the Energy Consumption/Production and Its Uncertainties Driven by Meteorological Observations and Forecasts," Sustainability, MDPI, vol. 11(12), pages 1-22, June.
  797. Qian Cheng & Honggang Xu & Shuaipeng Fei & Zongpeng Li & Zhen Chen, 2022. "Estimation of Maize LAI Using Ensemble Learning and UAV Multispectral Imagery under Different Water and Fertilizer Treatments," Agriculture, MDPI, vol. 12(8), pages 1-21, August.
  798. Conner Mullally & Mayra Rivas & Travis McArthur, 2021. "Using Machine Learning to Estimate the Heterogeneous Effects of Livestock Transfers," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1058-1081, May.
  799. Hyun Hak Kim & Norman Swanson, 2013. "Mining Big Data Using Parsimonious Factor and Shrinkage Methods," Departmental Working Papers 201316, Rutgers University, Department of Economics.
  800. Gayatri Kawlra & Kazuki Sakamoto, 2023. "Spatialising urban health vulnerability: An analysis of NYC’s critical infrastructure during COVID-19," Urban Studies, Urban Studies Journal Limited, vol. 60(9), pages 1629-1649, July.
  801. Akey, Pat & Grégoire, Vincent & Martineau, Charles, 2022. "Price revelation from insider trading: Evidence from hacked earnings news," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1162-1184.
  802. He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
  803. Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
  804. Sariyar Murat & Schumacher Martin & Binder Harald, 2014. "A boosting approach for adapting the sparsity of risk prediction signatures based on different molecular levels," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(3), pages 1-15, June.
  805. Huang, Zhensheng & Pang, Zhen & Lin, Bingqing & Shao, Quanxi, 2014. "Model structure selection in single-index-coefficient regression models," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 159-175.
  806. Kwon, Sunghoon & Oh, Seungyoung & Lee, Youngjo, 2016. "The use of random-effect models for high-dimensional variable selection problems," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 401-412.
  807. Nicolas Ledru & Parker C. Wilson & Yoshiharu Muto & Yasuhiro Yoshimura & Haojia Wu & Dian Li & Amish Asthana & Stefan G. Tullius & Sushrut S. Waikar & Giuseppe Orlando & Benjamin D. Humphreys, 2024. "Predicting proximal tubule failed repair drivers through regularized regression analysis of single cell multiomic sequencing," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
  808. Tan, Xin Lu, 2019. "Optimal estimation of slope vector in high-dimensional linear transformation models," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 179-204.
  809. Kubus Mariusz, 2016. "Locally Regularized Linear Regression in the Valuation of Real Estate," Statistics in Transition New Series, Polish Statistical Association, vol. 17(3), pages 515-524, September.
  810. Oguzhan Cepni & Ibrahim Ethem Guney & Doruk Kucuksarac & M. Hasan Yilmaz, 2021. "Do local and global factors impact the emerging markets' sovereign yield curves? Evidence from a data‐rich environment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1214-1229, November.
  811. Kamiar Rahnama Rad & Arian Maleki, 2020. "A scalable estimate of the out‐of‐sample prediction error via approximate leave‐one‐out cross‐validation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(4), pages 965-996, September.
  812. Yunfeng Zhang & Irina Gaynanova, 2022. "Joint association and classification analysis of multi‐view data," Biometrics, The International Biometric Society, vol. 78(4), pages 1614-1625, December.
  813. Katsuhiro Tanaka & Rei Yamamoto, 2023. "Ellipsoidal buffered area under the curve maximization model with variable selection in credit risk estimation," Computational Management Science, Springer, vol. 20(1), pages 1-28, December.
  814. Qile Dai & Geyu Zhou & Hongyu Zhao & Urmo Võsa & Lude Franke & Alexis Battle & Alexander Teumer & Terho Lehtimäki & Olli T. Raitakari & Tõnu Esko & Michael P. Epstein & Jingjing Yang, 2023. "OTTERS: a powerful TWAS framework leveraging summary-level reference data," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
  815. Matthew Hindman, 2015. "Building Better Models," The ANNALS of the American Academy of Political and Social Science, , vol. 659(1), pages 48-62, May.
  816. Hao, Xianfeng & Zhao, Yuyang & Wang, Yudong, 2020. "Forecasting the real prices of crude oil using robust regression models with regularization constraints," Energy Economics, Elsevier, vol. 86(C).
  817. Xing, Xin & Hu, Jinjin & Yang, Yaning, 2014. "Robust minimum variance portfolio with L-infinity constraints," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 107-117.
  818. Banerjee, Sayantan, 2022. "Horseshoe shrinkage methods for Bayesian fusion estimation," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
  819. Luai Al-Labadi & Hrithik Kumar Advani & Brittani Holder & Kyuson Lim, 2023. "Education Influential Factors of University Attendance," Journal of Educational and Developmental Psychology, Canadian Center of Science and Education, vol. 13(1), pages 1-29, May.
  820. Hojin Yang & Hongtu Zhu & Joseph G. Ibrahim, 2018. "MILFM: Multiple index latent factor model based on high‐dimensional features," Biometrics, The International Biometric Society, vol. 74(3), pages 834-844, September.
  821. Luis A. Barboza & Julien Emile-Geay & Bo Li & Wan He, 2019. "Efficient Reconstructions of Common Era Climate via Integrated Nested Laplace Approximations," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(3), pages 535-554, September.
  822. Krüger, Jens & Ruths Sion, Sebastian, 2019. "Improving oil price forecasts by sparse VAR methods," Darmstadt Discussion Papers in Economics 237, Darmstadt University of Technology, Department of Law and Economics.
  823. Štefan Lyócsa & Petra Vašaničová & Branka Hadji Misheva & Marko Dávid Vateha, 2022. "Default or profit scoring credit systems? Evidence from European and US peer-to-peer lending markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
  824. Christian S Göbl & Latife Bozkurt & Andrea Tura & Giovanni Pacini & Alexandra Kautzky-Willer & Martina Mittlböck, 2015. "Application of Penalized Regression Techniques in Modelling Insulin Sensitivity by Correlated Metabolic Parameters," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-19, November.
  825. Qifa Xu & Junqing Zuo & Cuixia Jiang & Yaoyao He, 2021. "A large constrained time‐varying portfolio selection model with DCC‐MIDAS: Evidence from Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3417-3435, July.
  826. International Monetary Fund, 2018. "Euro Area Policies: Financial Sector Assessment Program-Technical Note-Systemic Risk Analysis," IMF Staff Country Reports 2018/231, International Monetary Fund.
  827. Sparkle Springfield & Feifei Qin & Haley Hedlin & Charles B. Eaton & Milagros C. Rosal & Herman Taylor & Ursula M. Staudinger & Marcia L. Stefanick, 2022. "Modifiable Resources and Resilience in Racially and Ethnically Diverse Older Women: Implications for Health Outcomes and Interventions," IJERPH, MDPI, vol. 19(12), pages 1-19, June.
  828. Yao, Xingzhi & Izzeldin, Marwan & Li, Zhenxiong, 2019. "A novel cluster HAR-type model for forecasting realized volatility," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1318-1331.
  829. repec:jss:jstsof:33:i01 is not listed on IDEAS
  830. Guo, Xu & Lin, Hai & Wu, Chunchi & Zhou, Guofu, 2022. "Predictive information in corporate bond yields," Journal of Financial Markets, Elsevier, vol. 59(PB).
  831. Byungjoo Noh & Hyemin Yoon & Changhong Youm & Sangjin Kim & Myeounggon Lee & Hwayoung Park & Bohyun Kim & Hyejin Choi & Yoonjae Noh, 2021. "Prediction of Decline in Global Cognitive Function Using Machine Learning with Feature Ranking of Gait and Physical Fitness Outcomes in Older Adults," IJERPH, MDPI, vol. 18(21), pages 1-16, October.
  832. George Milunovich, 2020. "Forecasting Australia's real house price index: A comparison of time series and machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1098-1118, November.
  833. Ujjwal Das & Kalyan Das, 2021. "Selection of influential variables in ordinal data with preponderance of zeros," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(1), pages 66-87, February.
  834. Hiba Alawieh & Nicolas Wicker & Baydaa Al Ayoubi & Luc Moulinier, 2017. "Penalized multidimensional fitting for protein movement detection," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(15), pages 2697-2715, November.
  835. Zhenyu Zhuo & Ershun Du & Ning Zhang & Chris P. Nielsen & Xi Lu & Jinyu Xiao & Jiawei Wu & Chongqing Kang, 2022. "Cost increase in the electricity supply to achieve carbon neutrality in China," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
  836. Karin Wolffhechel & Amanda C Hahn & Hanne Jarmer & Claire I Fisher & Benedict C Jones & Lisa M DeBruine, 2015. "Testing the Utility of a Data-Driven Approach for Assessing BMI from Face Images," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-10, October.
  837. Indy Man Kit Ho & Kai Yuen Cheong & Anthony Weldon, 2021. "Predicting student satisfaction of emergency remote learning in higher education during COVID-19 using machine learning techniques," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-27, April.
  838. Koen W. de Bock, 2017. "The best of two worlds: Balancing model strength and comprehensibility in business failure prediction using spline-rule ensembles," Post-Print hal-01588059, HAL.
  839. Qiao Wen Tan & Peng Ken Lim & Zhong Chen & Asher Pasha & Nicholas Provart & Marius Arend & Zoran Nikoloski & Marek Mutwil, 2023. "Cross-stress gene expression atlas of Marchantia polymorpha reveals the hierarchy and regulatory principles of abiotic stress responses," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
  840. Andrea G Allegrini & Ville Karhunen & Jonathan R I Coleman & Saskia Selzam & Kaili Rimfeld & Sophie von Stumm & Jean-Baptiste Pingault & Robert Plomin, 2020. "Multivariable G-E interplay in the prediction of educational achievement," PLOS Genetics, Public Library of Science, vol. 16(11), pages 1-20, November.
  841. Liu, Bing-Yue & Fan, Ying & Ji, Qiang & Hussain, Nazim, 2022. "High-dimensional CoVaR network connectedness for measuring conditional financial contagion and risk spillovers from oil markets to the G20 stock system," Energy Economics, Elsevier, vol. 105(C).
  842. Samuel N. Cohen & Silvia Lui & Will Malpass & Giulia Mantoan & Lars Nesheim & 'Aureo de Paula & Andrew Reeves & Craig Scott & Emma Small & Lingyi Yang, 2023. "Nowcasting with signature methods," Papers 2305.10256, arXiv.org.
  843. Eraslan, Sercan & Nöller, Marvin, 2020. "Recession probabilities falling from the STARs," Discussion Papers 08/2020, Deutsche Bundesbank.
  844. Juan Carlos Laria & Line H. Clemmensen & Bjarne K. Ersbøll & David Delgado-Gómez, 2022. "A Generalized Linear Joint Trained Framework for Semi-Supervised Learning of Sparse Features," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
  845. Peter Martey Addo & Dominique Guégan & Bertrand Hassani, 2018. "Credit Risk Analysis using Machine and Deep learning models," Documents de travail du Centre d'Economie de la Sorbonne 18003, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  846. Wei Wang & Linjian Li & Sheng Li & Fei Yin & Fang Liao & Tao Zhang & Xiaosong Li & Xiong Xiao & Yue Ma, 2022. "Average ordinary least squares‐centered penalized regression: A more efficient way to address multicollinearity than ridge regression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 76(3), pages 347-368, August.
  847. K. Kampa & S. Mehta & C. Chou & W. Chaovalitwongse & T. Grabowski, 2014. "Sparse optimization in feature selection: application in neuroimaging," Journal of Global Optimization, Springer, vol. 59(2), pages 439-457, July.
  848. Feng Li & Lu Lin & Yuxia Su, 2013. "Variable selection and parameter estimation for partially linear models via Dantzig selector," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(2), pages 225-238, February.
  849. Patrick Ten Eyck & Joseph E. Cavanaugh, 2018. "Model selection criteria based on cross-validatory concordance statistics," Computational Statistics, Springer, vol. 33(2), pages 595-621, June.
  850. Aneiros, Germán & Novo, Silvia & Vieu, Philippe, 2022. "Variable selection in functional regression models: A review," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
  851. Román Salmerón Gómez & Catalina García García & José García Pérez, 2020. "Detection of Near-Nulticollinearity through Centered and Noncentered Regression," Mathematics, MDPI, vol. 8(6), pages 1-17, June.
  852. Wang, Chunzheng & Hu, Minghua & Yang, Lei & Zhao, Zheng, 2022. "Improving the spatial-temporal generalization of flight block time prediction: A development of stacking models," Journal of Air Transport Management, Elsevier, vol. 103(C).
  853. Jiawen Luo & Qun Zhang, 2024. "Air pollution, weather factors, and realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 151-217, February.
  854. Sai Wang & Hai-Wei Shen & Hua Chai & Yong Liang, 2019. "Complex harmonic regularization with differential evolution in a memetic framework for biomarker selection," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-21, February.
  855. Dong, Bing & Liu, Yapan & Fontenot, Hannah & Ouf, Mohamed & Osman, Mohamed & Chong, Adrian & Qin, Shuxu & Salim, Flora & Xue, Hao & Yan, Da & Jin, Yuan & Han, Mengjie & Zhang, Xingxing & Azar, Elie & , 2021. "Occupant behavior modeling methods for resilient building design, operation and policy at urban scale: A review," Applied Energy, Elsevier, vol. 293(C).
  856. Niloy Biswas & Anirban Bhattacharya & Pierre E. Jacob & James E. Johndrow, 2022. "Coupling‐based convergence assessment of some Gibbs samplers for high‐dimensional Bayesian regression with shrinkage priors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 973-996, July.
  857. Hyungrok Do & Shinjini Nandi & Preston Putzel & Padhraic Smyth & Judy Zhong, 2023. "A joint fairness model with applications to risk predictions for underrepresented populations," Biometrics, The International Biometric Society, vol. 79(2), pages 826-840, June.
  858. Jan Pablo Burgard & Joscha Krause & Dennis Kreber, 2019. "Regularized Area-level Modelling for Robust Small Area Estimation in the Presence of Unknown Covariate Measurement Errors," Research Papers in Economics 2019-04, University of Trier, Department of Economics.
  859. Akey, Pat & Grégoire, Vincent & Martineau, Charles, 2021. "Price Revelation from Insider Trading: Evidence from Hacked Earnings News," SocArXiv qe6tu, Center for Open Science.
  860. Lushi Chen & Tao Gong & Michal Kosinski & David Stillwell & Robert L Davidson, 2017. "Building a profile of subjective well-being for social media users," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-15, November.
  861. Li, Jianan & Han, Xiaoyi, 2019. "Bayesian Lassos for spatial durbin error model with smoothness prior: Application to detect spillovers of China's treaty ports," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 38-74.
  862. Marc Gürtler & Marvin Zöllner, 2023. "Heterogeneities among credit risk parameter distributions: the modality defines the best estimation method," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 251-287, March.
  863. Bilin Zeng & Xuerong Meggie Wen & Lixing Zhu, 2017. "A link-free sparse group variable selection method for single-index model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(13), pages 2388-2400, October.
  864. Ali Habibnia & Esfandiar Maasoumi, 2021. "Forecasting in Big Data Environments: An Adaptable and Automated Shrinkage Estimation of Neural Networks (AAShNet)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 363-381, December.
  865. Jonathan Boss & Alexander Rix & Yin‐Hsiu Chen & Naveen N. Narisetty & Zhenke Wu & Kelly K. Ferguson & Thomas F. McElrath & John D. Meeker & Bhramar Mukherjee, 2021. "A hierarchical integrative group least absolute shrinkage and selection operator for analyzing environmental mixtures," Environmetrics, John Wiley & Sons, Ltd., vol. 32(8), December.
  866. Jeremy D. Turiel & Tomaso Aste, 2019. "P2P Loan acceptance and default prediction with Artificial Intelligence," Papers 1907.01800, arXiv.org.
  867. Li Shaoyu & Lu Qing & Fu Wenjiang & Romero Roberto & Cui Yuehua, 2009. "A Regularized Regression Approach for Dissecting Genetic Conflicts that Increase Disease Risk in Pregnancy," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-28, October.
  868. Li, Xingxiang & Cheng, Guosheng & Wang, Liming & Lai, Peng & Song, Fengli, 2017. "Ultrahigh dimensional feature screening via projection," Computational Statistics & Data Analysis, Elsevier, vol. 114(C), pages 88-104.
  869. Mishra, Aditya & Dey, Dipak K. & Chen, Yong & Chen, Kun, 2021. "Generalized co-sparse factor regression," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
  870. Georg Keilbar & Weining Wang, 2022. "Modelling systemic risk using neural network quantile regression," Empirical Economics, Springer, vol. 62(1), pages 93-118, January.
  871. Fenghua Li & Peida Xu & Shichun Zheng & Wenfeng Chen & Yang Yan & Suo Lu & Zhengkui Liu, 2018. "Photoplethysmography based psychological stress detection with pulse rate variability feature differences and elastic net," International Journal of Distributed Sensor Networks, , vol. 14(9), pages 15501477188, September.
  872. Xia, X.H. & Huang, G.T. & Chen, G.Q. & Zhang, Bo & Chen, Z.M. & Yang, Q., 2011. "Energy security, efficiency and carbon emission of Chinese industry," Energy Policy, Elsevier, vol. 39(6), pages 3520-3528, June.
  873. Jason Xu & Eric C. Chi & Meng Yang & Kenneth Lange, 2018. "A majorization–minimization algorithm for split feasibility problems," Computational Optimization and Applications, Springer, vol. 71(3), pages 795-828, December.
  874. Wang,Dieter & Andree,Bo Pieter Johannes & Chamorro Elizondo,Andres Fernando & Spencer,Phoebe Girouard, 2020. "Stochastic Modeling of Food Insecurity," Policy Research Working Paper Series 9413, The World Bank.
  875. Cai, Xizhen & Zhu, Yeying & Huang, Yuan & Ghosh, Debashis, 2022. "High-dimensional causal mediation analysis based on partial linear structural equation models," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
  876. Yoshiki Nakajima & Naoya Sueishi, 2022. "Forecasting the Japanese macroeconomy using high-dimensional data," The Japanese Economic Review, Springer, vol. 73(2), pages 299-324, April.
  877. F. S. Nathoo & A. Babul & A. Moiseev & N. Virji-Babul & M. F. Beg, 2014. "A variational Bayes spatiotemporal model for electromagnetic brain mapping," Biometrics, The International Biometric Society, vol. 70(1), pages 132-143, March.
  878. Michoel, Tom, 2016. "Natural coordinate descent algorithm for L1-penalised regression in generalised linear models," Computational Statistics & Data Analysis, Elsevier, vol. 97(C), pages 60-70.
  879. Shi, Guiling & Lim, Chae Young & Maiti, Tapabrata, 2019. "Bayesian model selection for generalized linear models using non-local priors," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 285-296.
  880. Vera Wendler-Bosco & Charles Nicholson, 2022. "Modeling the economic impact of incoming tropical cyclones using machine learning," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(1), pages 487-518, January.
  881. Vinny Davies & Richard Reeve & William T. Harvey & Francois F. Maree & Dirk Husmeier, 2017. "A sparse hierarchical Bayesian model for detecting relevant antigenic sites in virus evolution," Computational Statistics, Springer, vol. 32(3), pages 803-843, September.
  882. Li, Mei & Kong, Lingchen, 2019. "Double fused Lasso penalized LAD for matrix regression," Applied Mathematics and Computation, Elsevier, vol. 357(C), pages 119-138.
  883. Gür Ali, Özden & Gürlek, Ragıp, 2020. "Automatic Interpretable Retail forecasting with promotional scenarios," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1389-1406.
  884. McKay Curtis, S. & Banerjee, Sayantan & Ghosal, Subhashis, 2014. "Fast Bayesian model assessment for nonparametric additive regression," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 347-358.
  885. Sun, Fei & Zhang, Qi, 2023. "Robust transfer learning of high-dimensional generalized linear model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
  886. Mariarosaria Comunale, 2020. "The persistently high rate of suicide in Lithuania: an updated view," Bank of Lithuania Discussion Paper Series 21, Bank of Lithuania.
  887. Bommes, Elisabeth & Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl, 2018. "Textual Sentiment and Sector specific reaction," IRTG 1792 Discussion Papers 2018-043, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  888. Sermpinis, Georgios & Tsoukas, Serafeim & Zhang, Ping, 2018. "Modelling market implied ratings using LASSO variable selection techniques," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 19-35.
  889. Katherine Casey & Abou Bakarr Kamara & Niccoló Meriggi, 2019. "An Experiment in Candidate Selection," NBER Working Papers 26160, National Bureau of Economic Research, Inc.
  890. Lourenço, Nuno & Gouveia, Carlos Melo & Rua, António, 2021. "Forecasting tourism with targeted predictors in a data-rich environment," Economic Modelling, Elsevier, vol. 96(C), pages 445-454.
  891. Petrella, Lea & Raponi, Valentina, 2019. "Joint estimation of conditional quantiles in multivariate linear regression models with an application to financial distress," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 70-84.
  892. Niu, Zibo & Wang, Chenlu & Zhang, Hongwei, 2023. "Forecasting stock market volatility with various geopolitical risks categories: New evidence from machine learning models," International Review of Financial Analysis, Elsevier, vol. 89(C).
  893. Peter Bühlmann & Jacopo Mandozzi, 2014. "High-dimensional variable screening and bias in subsequent inference, with an empirical comparison," Computational Statistics, Springer, vol. 29(3), pages 407-430, June.
  894. Audrino, Francesco & Tetereva, Anastasija, 2019. "Sentiment spillover effects for US and European companies," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 542-567.
  895. Su, Miaomiao & Wang, Qihua, 2022. "A convex programming solution based debiased estimator for quantile with missing response and high-dimensional covariables," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
  896. Chris Gennings & Katherine Svensson & Alicja Wolk & Christian Lindh & Hannu Kiviranta & Carl-Gustaf Bornehag, 2022. "Using Metrics of a Mixture Effect and Nutrition from an Observational Study for Consideration towards Causal Inference," IJERPH, MDPI, vol. 19(4), pages 1-15, February.
  897. Daniel Ambach & Carsten Croonenbroeck, 2016. "Space-time short- to medium-term wind speed forecasting," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 5-20, March.
  898. Phil Henrickson, 2020. "Predicting the costs of war," The Journal of Defense Modeling and Simulation, , vol. 17(3), pages 285-308, July.
  899. Wanling Xie & Hu Yang, 2023. "Group sparse recovery via group square-root elastic net and the iterative multivariate thresholding-based algorithm," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(3), pages 469-507, September.
  900. Peter Martey Addo & Dominique Guegan & Bertrand Hassani, 2018. "Credit Risk Analysis Using Machine and Deep Learning Models," Risks, MDPI, vol. 6(2), pages 1-20, April.
  901. Wei Sun & Lexin Li, 2012. "Multiple Loci Mapping via Model-free Variable Selection," Biometrics, The International Biometric Society, vol. 68(1), pages 12-22, March.
  902. Wookjae Heo & Eunchan Kim & Eun Jin Kwak & John E. Grable, 2024. "Identifying Hidden Factors Associated with Household Emergency Fund Holdings: A Machine Learning Application," Mathematics, MDPI, vol. 12(2), pages 1-39, January.
  903. Young Joo Yoon & Cheolwoo Park & Erik Hofmeister & Sangwook Kang, 2012. "Group variable selection in cardiopulmonary cerebral resuscitation data for veterinary patients," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(7), pages 1605-1621, January.
  904. Téllez-León, Isela-Elizabeth & Martínez-Jaramillo, Serafín & O. L. Escobar-Farfán, Luis & Hochreiter, Ronald, 2021. "How are network centrality metrics related to interest rates in the Mexican secured and unsecured interbank markets?," Journal of Financial Stability, Elsevier, vol. 55(C).
  905. Masatoshi Goda, 2023. "Sparse estimation for generalized exponential marked Hawkes process," Statistical Inference for Stochastic Processes, Springer, vol. 26(1), pages 139-169, April.
  906. Latouche, Pierre & Mattei, Pierre-Alexandre & Bouveyron, Charles & Chiquet, Julien, 2016. "Combining a relaxed EM algorithm with Occam’s razor for Bayesian variable selection in high-dimensional regression," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 177-190.
  907. Jingying Yang & Guishu Bai & Mei Yan, 2023. "Minimum Residual Sum of Squares Estimation Method for High-Dimensional Partial Correlation Coefficient," Mathematics, MDPI, vol. 11(20), pages 1-22, October.
  908. Liqun Yu & Nan Lin, 2017. "ADMM for Penalized Quantile Regression in Big Data," International Statistical Review, International Statistical Institute, vol. 85(3), pages 494-518, December.
  909. Ding, Jiayi & Zhou, Jianfang & Cai, Wei, 2023. "An efficient variable selection-based Kriging model method for the reliability analysis of slopes with spatially variable soils," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
  910. Zhang, Siliang & Chen, Yunxiao, 2022. "Computation for latent variable model estimation: a unified stochastic proximal framework," LSE Research Online Documents on Economics 114489, London School of Economics and Political Science, LSE Library.
  911. Heng Lian & Xin Chen & Jian-Yi Yang, 2012. "Identification of Partially Linear Structure in Additive Models with an Application to Gene Expression Prediction from Sequences," Biometrics, The International Biometric Society, vol. 68(2), pages 437-445, June.
  912. Jiahan Li & Ilias Tsiakas & Wei Wang, 2015. "Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 293-341.
  913. Tomáš Bunčák, 2016. "Exchange Rates Forecasting: Can Jump Models Combined with Macroeconomic Fundamentals Help?," Prague Economic Papers, Prague University of Economics and Business, vol. 2016(5), pages 527-546.
  914. Sean M Gibbons & Sean M Kearney & Chris S Smillie & Eric J Alm, 2017. "Two dynamic regimes in the human gut microbiome," PLOS Computational Biology, Public Library of Science, vol. 13(2), pages 1-20, February.
  915. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
  916. Micha{l} Narajewski & Florian Ziel, 2018. "Econometric modelling and forecasting of intraday electricity prices," Papers 1812.09081, arXiv.org, revised Sep 2019.
  917. Wit, Ernst C., 2018. "Big data and biostatistics: The death of the asymptotic Valhalla," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 30-33.
  918. Lansangan, Joseph Ryan G. & Barrios, Erniel B., 2017. "Simultaneous dimension reduction and variable selection in modeling high dimensional data," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 242-256.
  919. Jan Pablo Burgard & Joscha Krause & Dennis Kreber & Domingo Morales, 2021. "The generalized equivalence of regularization and min–max robustification in linear mixed models," Statistical Papers, Springer, vol. 62(6), pages 2857-2883, December.
  920. Chao Liang & Yu Wei & Likun Lei & Feng Ma, 2022. "Global equity market volatility forecasting: New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 594-609, January.
  921. Baaken, Dominik & Hess, Sebastian, 2021. "Forecasting Regional Milk Production Quantity: A Comparison of Regression Models and Machine Learning," 2021 Conference, August 17-31, 2021, Virtual 315117, International Association of Agricultural Economists.
  922. Bousebata, Meryem & Enjolras, Geoffroy & Girard, Stéphane, 2023. "Extreme partial least-squares," Journal of Multivariate Analysis, Elsevier, vol. 194(C).
  923. Sheng, Ying & Wang, Qihua, 2020. "Model-free feature screening for ultrahigh dimensional classification," Journal of Multivariate Analysis, Elsevier, vol. 178(C).
  924. Chakraborty, Sounak & Guo, Ruixin, 2011. "A Bayesian hybrid Huberized support vector machine and its applications in high-dimensional medical data," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1342-1356, March.
  925. van Wieringen, Wessel N. & Kun, David & Hampel, Regina & Boulesteix, Anne-Laure, 2009. "Survival prediction using gene expression data: A review and comparison," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1590-1603, March.
  926. Zeyu Diao & Lili Yue & Fanrong Zhao & Gaorong Li, 2022. "High-Dimensional Regression Adjustment Estimation for Average Treatment Effect with Highly Correlated Covariates," Mathematics, MDPI, vol. 10(24), pages 1-18, December.
  927. Niţoi, Mihai & Pochea, Maria Miruna, 2022. "The nexus between bank connectedness and investors’ sentiment," Finance Research Letters, Elsevier, vol. 44(C).
  928. Holter, Julia C. & Stallrich, Jonathan W., 2023. "Tuning parameter selection for penalized estimation via R2," Computational Statistics & Data Analysis, Elsevier, vol. 183(C).
  929. Gabriel Okasa, 2022. "Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance," Papers 2201.12692, arXiv.org.
  930. Tanin Sirimongkolkasem & Reza Drikvandi, 2019. "On Regularisation Methods for Analysis of High Dimensional Data," Annals of Data Science, Springer, vol. 6(4), pages 737-763, December.
  931. Amir Beck & Yehonathan Refael, 2022. "Sparse regularization via bidualization," Journal of Global Optimization, Springer, vol. 82(3), pages 463-482, March.
  932. Hood, Rick & Grant, Robert & Jones, Ray & Goldacre, Allie, 2016. "A study of performance indicators and Ofsted ratings in English child protection services," Children and Youth Services Review, Elsevier, vol. 67(C), pages 50-56.
  933. Joldes, Grand Roman & Chowdhury, Habibullah Amin & Wittek, Adam & Doyle, Barry & Miller, Karol, 2015. "Modified moving least squares with polynomial bases for scattered data approximation," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 893-902.
  934. Jacob Bergstedt & Sadoune Ait Kaci Azzou & Kristin Tsuo & Anthony Jaquaniello & Alejandra Urrutia & Maxime Rotival & David T. S. Lin & Julia L. MacIsaac & Michael S. Kobor & Matthew L. Albert & Darrag, 2022. "The immune factors driving DNA methylation variation in human blood," Nature Communications, Nature, vol. 13(1), pages 1-20, December.
  935. Bert De Reyck & Ioannis Fragkos & Yael Grushka-Cockayne & Casey Lichtendahl & Hammond Guerin & Andrew Kritzer, 2017. "Vungle Inc. Improves Monetization Using Big Data Analytics," Interfaces, INFORMS, vol. 47(5), pages 454-466, October.
  936. Paweł Teisseyre & Robert A. Kłopotek & Jan Mielniczuk, 2016. "Random Subspace Method for high-dimensional regression with the R package regRSM," Computational Statistics, Springer, vol. 31(3), pages 943-972, September.
  937. Tulin Guzel & Hakan Cinar & Mehmet Nabi Cenet & Kamil Doruk Oguz & Ahmet Yucekaya & Mustafa Hekimoglu, 2023. "A Framework to Forecast Electricity Consumption of Meters using Automated Ranking and Data Preprocessing," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 179-193, September.
  938. Daniel Borup & Jorge Wolfgang Hansen & Benjamin Dybro Liengaard & Erik Christian Montes Schütte, 2023. "Quantifying investor narratives and their role during COVID‐19," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 512-532, June.
  939. W. Braun, 2015. "Visualization of evidence in regression with the QR decomposition," Computational Statistics, Springer, vol. 30(4), pages 907-927, December.
  940. Yu, Jisang & Vandeveer, Monte & Volesky, Jerry, 2017. "Basis Risk and Effectiveness of Rainfall Index Insurance for Pasture, Rangeland and Forage," SCC-76 Meeting, 2017, March 30-April 1, Pensacola, Florida 256327, SCC-76: Economics and Management of Risk in Agriculture and Natural Resources.
  941. Kreutzmann, Ann-Kristin & Marek, Philipp & Salvati, Nicola & Schmid, Timo, 2019. "Estimating regional wealth in Germany: How different are East and West really?," Discussion Papers 35/2019, Deutsche Bundesbank.
  942. Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
  943. Kascha, Christian & Trenkler, Carsten, 2015. "Forecasting VARs, model selection, and shrinkage," Working Papers 15-07, University of Mannheim, Department of Economics.
  944. Carina Moreira Costa & Dennis Kreber & Martin Schmidt, 2022. "An Alternating Method for Cardinality-Constrained Optimization: A Computational Study for the Best Subset Selection and Sparse Portfolio Problems," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 2968-2988, November.
  945. Weihua Zhao & Riquan Zhang & Jicai Liu & Yazhao Lv, 2014. "Robust and efficient variable selection for semiparametric partially linear varying coefficient model based on modal regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(1), pages 165-191, February.
  946. Tiffany Elsten & Mark Rooij, 2022. "SUBiNN: a stacked uni- and bivariate kNN sparse ensemble," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(4), pages 847-874, December.
  947. Gao, Qishuo & Shi, Vivien & Pettit, Christopher & Han, Hoon, 2022. "Property valuation using machine learning algorithms on statistical areas in Greater Sydney, Australia," Land Use Policy, Elsevier, vol. 123(C).
  948. Nott, David J. & Leng, Chenlei, 2010. "Bayesian projection approaches to variable selection in generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3227-3241, December.
  949. Shuang Huang & Chengcheng Hu & Melanie L. Bell & Dean Billheimer & Stefano Guerra & Denise Roe & Monica M. Vasquez & Edward J. Bedrick, 2018. "Regularized continuous‐time Markov Model via elastic net," Biometrics, The International Biometric Society, vol. 74(3), pages 1045-1054, September.
  950. Bingxin Zhao & Fei Zou & Hongtu Zhu, 2023. "Cross‐trait prediction accuracy of summary statistics in genome‐wide association studies," Biometrics, The International Biometric Society, vol. 79(2), pages 841-853, June.
  951. Sophie Lambert-Lacroix & Laurent Zwald, 2016. "The adaptive BerHu penalty in robust regression," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(3), pages 487-514, September.
  952. Yanming Li & Bin Nan & Ji Zhu, 2015. "Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure," Biometrics, The International Biometric Society, vol. 71(2), pages 354-363, June.
  953. Zemin Zheng & Jinchi Lv & Wei Lin, 2021. "Nonsparse Learning with Latent Variables," Operations Research, INFORMS, vol. 69(1), pages 346-359, January.
  954. Daniela M. Witten & Robert Tibshirani, 2009. "Covariance‐regularized regression and classification for high dimensional problems," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 615-636, June.
  955. Mingqiu Wang & Guo-Liang Tian, 2016. "Robust group non-convex estimations for high-dimensional partially linear models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(1), pages 49-67, March.
  956. Capanu, Marinela & Giurcanu, Mihai & Begg, Colin B. & Gönen, Mithat, 2023. "Subsampling based variable selection for generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 184(C).
  957. Lai , Jennifer & McNelis, Paul, 2019. "Offshore Fears and Onshore Risk: Exchange Rate Pressures and Bank Volatility Contagion in the People’s Republic of China," ADB Economics Working Paper Series 602, Asian Development Bank.
  958. Howard D. Bondell & Brian J. Reich, 2012. "Consistent High-Dimensional Bayesian Variable Selection via Penalized Credible Regions," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1610-1624, December.
  959. Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kang, Miao & Kapadia, Sujit & Simsek, Özgür, 2020. "Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach," Bank of England working papers 848, Bank of England.
  960. Fabian Schäfer & Manuel Walther & Dominik G. Grimm & Alexander Hübner, 2023. "Combining machine learning and optimization for the operational patient-bed assignment problem," Health Care Management Science, Springer, vol. 26(4), pages 785-806, December.
  961. Zheng, Zemin & Li, Yang & Yu, Chongxiu & Li, Gaorong, 2018. "Balanced estimation for high-dimensional measurement error models," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 78-91.
  962. Yu-Min Yen, 2010. "A Note on Sparse Minimum Variance Portfolios and Coordinate-Wise Descent Algorithms," Papers 1005.5082, arXiv.org, revised Sep 2013.
  963. Abhinav Kaushik & Diane Dunham & Xiaorui Han & Evan Do & Sandra Andorf & Sheena Gupta & Andrea Fernandes & Laurie Elizabeth Kost & Sayantani B. Sindher & Wong Yu & Mindy Tsai & Robert Tibshirani & Sco, 2022. "CD8+ T cell differentiation status correlates with the feasibility of sustained unresponsiveness following oral immunotherapy," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  964. Chakraborty, Sounak & Lozano, Aurelie C., 2019. "A graph Laplacian prior for Bayesian variable selection and grouping," Computational Statistics & Data Analysis, Elsevier, vol. 136(C), pages 72-91.
  965. Thomas Falconer & Jalal Kazempour & Pierre Pinson, 2023. "Towards Replication-Robust Analytics Markets," Papers 2310.06000, arXiv.org, revised Feb 2024.
  966. Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2013. "Complete subset regressions," Journal of Econometrics, Elsevier, vol. 177(2), pages 357-373.
  967. Thuc Duy Le & Junpeng Zhang & Lin Liu & Huawen Liu & Jiuyong Li, 2015. "miRLAB: An R Based Dry Lab for Exploring miRNA-mRNA Regulatory Relationships," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-15, December.
  968. Wenli Huang & Yuchao Tang & Meng Wen & Haiyang Li, 2022. "Relaxed Variable Metric Primal-Dual Fixed-Point Algorithm with Applications," Mathematics, MDPI, vol. 10(22), pages 1-16, November.
  969. Yanxin Wang & Qibin Fan & Li Zhu, 2018. "Variable selection and estimation using a continuous approximation to the $$L_0$$ L 0 penalty," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(1), pages 191-214, February.
  970. Rajiv Sambasivan & Sourish Das & Sujit K. Sahu, 2020. "A Bayesian perspective of statistical machine learning for big data," Computational Statistics, Springer, vol. 35(3), pages 893-930, September.
  971. Yael Steuerman & Irit Gat-Viks, 2016. "Exploiting Gene-Expression Deconvolution to Probe the Genetics of the Immune System," PLOS Computational Biology, Public Library of Science, vol. 12(4), pages 1-22, April.
  972. Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
  973. Xuekui Zhang & Yuying Huang & Ke Xu & Li Xing, 2023. "Novel modelling strategies for high-frequency stock trading data," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-25, December.
  974. Phyllis Asorh Oteng & Victor Curtis Lartey & Amos Kwasi Amofa, 2023. "Modeling the Macroeconomic and Demographic Determinants of Life Insurance Demand in Ghana Using the Elastic Net Algorithm," SAGE Open, , vol. 13(3), pages 21582440231, September.
  975. Keith Knight, 2016. "The Penalized Analytic Center Estimator," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1471-1484, December.
  976. Shanshan Qin & Hao Ding & Yuehua Wu & Feng Liu, 2021. "High-dimensional sign-constrained feature selection and grouping," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 787-819, August.
  977. McMahan Christopher & Bridges William & Joyner Chase & Lund Robert & Baurley James & Kacamarga Muhamad Fitra & Pardamean Carissa & Pardamean Bens, 2017. "A Bayesian hierarchical model for identifying significant polygenic effects while controlling for confounding and repeated measures," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(5-6), pages 407-419, December.
  978. Graham Elliott & Allan Timmermann, 2016. "Forecasting in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 81-110, October.
  979. Nazila Pourhaji & Mohammad Asadpour & Ali Ahmadian & Ali Elkamel, 2022. "The Investigation of Monthly/Seasonal Data Clustering Impact on Short-Term Electricity Price Forecasting Accuracy: Ontario Province Case Study," Sustainability, MDPI, vol. 14(5), pages 1-14, March.
  980. Minerva Mukhopadhyay & David B. Dunson, 2020. "Targeted Random Projection for Prediction From High-Dimensional Features," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(532), pages 1998-2010, December.
  981. Tomáš Plíhal, 2021. "Scheduled macroeconomic news announcements and Forex volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1379-1397, December.
  982. Ping Zeng & Yongyue Wei & Yang Zhao & Jin Liu & Liya Liu & Ruyang Zhang & Jianwei Gou & Shuiping Huang & Feng Chen, 2014. "Variable selection approach for zero-inflated count data via adaptive lasso," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(4), pages 879-894, April.
  983. Roger Beecham & Nick Williams & Alexis Comber, 2020. "Regionally-structured explanations behind area-level populism: An update to recent ecological analyses," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-20, March.
  984. Nicolas Woloszko, 2020. "Tracking activity in real time with Google Trends," OECD Economics Department Working Papers 1634, OECD Publishing.
  985. Matthias Pelster & Johannes Vilsmeier, 2018. "The determinants of CDS spreads: evidence from the model space," Review of Derivatives Research, Springer, vol. 21(1), pages 63-118, April.
  986. Andreas Floren & Tobias Müller, 2023. "Using a Machine Learning Approach to Classify the Degree of Forest Management," Sustainability, MDPI, vol. 15(16), pages 1-14, August.
  987. Supareuk Tarapituxwong & Namchok Chimprang & Woraphon Yamaka & Piangtawan Polard, 2023. "A Lasso and Ridge-Cox Proportional Hazard Model Analysis of Thai Tourism Businesses’ Resilience and Survival in the COVID-19 Crisis," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
  988. Bian, Fengmiao & Zhang, Xiaoqun, 2021. "A parameterized Douglas–Rachford splitting algorithm for nonconvex optimization," Applied Mathematics and Computation, Elsevier, vol. 410(C).
  989. Emmanuel O. Ogundimu, 2022. "Regularization and variable selection in Heckman selection model," Statistical Papers, Springer, vol. 63(2), pages 421-439, April.
  990. Gefang, Deborah, 2014. "Bayesian doubly adaptive elastic-net Lasso for VAR shrinkage," International Journal of Forecasting, Elsevier, vol. 30(1), pages 1-11.
  991. Jaehyuk Choi & Desheng Ge & Kyu Ho Kang & Sungbin Sohn, 2023. "Yield spread selection in predicting recession probabilities," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1772-1785, November.
  992. Yang Liu & Francesca Chiaromonte & Bing Li, 2017. "Structured Ordinary Least Squares: A Sufficient Dimension Reduction approach for regressions with partitioned predictors and heterogeneous units," Biometrics, The International Biometric Society, vol. 73(2), pages 529-539, June.
  993. Caporin, Massimiliano & Poli, Francesco, 2022. "News and intraday jumps: Evidence from regularization and class imbalance," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
  994. Weng, Jiaying, 2022. "Fourier transform sparse inverse regression estimators for sufficient variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
  995. Michele Lalla & Patrizio Frederic, 2020. "Tertiary education decisions of immigrants and non-immigrants in Italy: an empirical approach," Department of Economics 0168, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
  996. Lucey, Brian & Urquhart, Andrew & Zhang, Hanxiong, 2022. "UK Vice Chancellor compensation: Do they get what they deserve?," The British Accounting Review, Elsevier, vol. 54(4).
  997. Ivan Stojkovic & Zoran Obradovic, 2017. "Sparse Learning of the Disease Severity Score for High-Dimensional Data," Complexity, Hindawi, vol. 2017, pages 1-11, December.
  998. Matsui, Hidetoshi, 2014. "Variable and boundary selection for functional data via multiclass logistic regression modeling," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 176-185.
  999. Mojtaba Ganjali & Taban Baghfalaki, 2018. "Application of Penalized Mixed Model in Identification of Genes in Yeast Cell-Cycle Gene Expression Data," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 6(2), pages 38-41, April.
  1000. Santiago Gamba-Santamaria & Luis Fernando Melo-Velandia & Camilo Orozco-Vanegas, 2021. "What can credit vintages tell us about non-performing loans?," Borradores de Economia 1154, Banco de la Republica de Colombia.
  1001. Kaida Cai & Hua Shen & Xuewen Lu, 2022. "Adaptive bi-level variable selection for multivariate failure time model with a diverging number of covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(4), pages 968-993, December.
  1002. Nguyen, Quyen & Diaz-Rainey, Ivan & Kuruppuarachchi, Duminda, 2021. "Predicting corporate carbon footprints for climate finance risk analyses: A machine learning approach," Energy Economics, Elsevier, vol. 95(C).
  1003. Xiaoping Liu & Xiao-Bai Li & Sumit Sarkar, 2023. "Cost-Restricted Feature Selection for Data Acquisition," Management Science, INFORMS, vol. 69(7), pages 3976-3992, July.
  1004. Masahiro Kato & Masaaki Imaizumi, 2023. "CATE Lasso: Conditional Average Treatment Effect Estimation with High-Dimensional Linear Regression," Papers 2310.16819, arXiv.org.
  1005. Di Nunno, Fabio & Granata, Francesco, 2023. "Future trends of reference evapotranspiration in Sicily based on CORDEX data and Machine Learning algorithms," Agricultural Water Management, Elsevier, vol. 280(C).
  1006. Adam Nowak & Patrick Smith, 2015. "Textual Analysis in Real Estate," Working Papers 15-34, Department of Economics, West Virginia University.
  1007. Karl B. Gregory & Dewei Wang & Christopher S. McMahan, 2019. "Adaptive elastic net for group testing," Biometrics, The International Biometric Society, vol. 75(1), pages 13-23, March.
  1008. Thiago Christiano Silva & Benjamin Miranda Tabak & Idamar Magalhães Ferreira, 2019. "Modeling Investor Behavior Using Machine Learning: Mean-Reversion and Momentum Trading Strategies," Complexity, Hindawi, vol. 2019, pages 1-14, December.
  1009. Gui-Hua Lin & Zhen-Ping Yang & Hai-An Yin & Jin Zhang, 2023. "A dual-based stochastic inexact algorithm for a class of stochastic nonsmooth convex composite problems," Computational Optimization and Applications, Springer, vol. 86(2), pages 669-710, November.
  1010. Peña, Daniel & Smucler, Ezequiel & Yohai, Victor J., 2021. "Sparse estimation of dynamic principal components for forecasting high-dimensional time series," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1498-1508.
  1011. Dominik Wolff & Ulrich Neugebauer, 2019. "Tree-based machine learning approaches for equity market predictions," Journal of Asset Management, Palgrave Macmillan, vol. 20(4), pages 273-288, July.
  1012. Wang, Qiao & Zhou, Wei & Feng, Y.T. & Ma, Gang & Cheng, Yonggang & Chang, Xiaolin, 2019. "An adaptive orthogonal improved interpolating moving least-square method and a new boundary element-free method," Applied Mathematics and Computation, Elsevier, vol. 353(C), pages 347-370.
  1013. Luo, Ruiyan & Qi, Xin, 2015. "Sparse wavelet regression with multiple predictive curves," Journal of Multivariate Analysis, Elsevier, vol. 134(C), pages 33-49.
  1014. Hyun Hak Kim, 2013. "Forecasting Macroeconomic Variables Using Data Dimension Reduction Methods: The Case of Korea," Working Papers 2013-26, Economic Research Institute, Bank of Korea.
  1015. Charlotte Soneson & Sarah Gerster & Mauro Delorenzi, 2014. "Batch Effect Confounding Leads to Strong Bias in Performance Estimates Obtained by Cross-Validation," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-13, June.
  1016. Michael Lechner, 2023. "Causal Machine Learning and its use for public policy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-15, December.
  1017. Junli Zhao & Fuqing Duan & Zhenkuan Pan & Zhongke Wu & Jinhua Li & Qingqiong Deng & Xiaona Li & Mingquan Zhou, 2017. "Craniofacial similarity analysis through sparse principal component analysis," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-18, June.
  1018. Tomáš Bunčák, . "Exchange Rates Forecasting: Can Jump Models Combined with Macroeconomic Fundamentals Help?," Prague Economic Papers, University of Economics, Prague, vol. 0, pages 1-20.
  1019. Petros C. Lazaridis & Ioannis E. Kavvadias & Konstantinos Demertzis & Lazaros Iliadis & Lazaros K. Vasiliadis, 2023. "Interpretable Machine Learning for Assessing the Cumulative Damage of a Reinforced Concrete Frame Induced by Seismic Sequences," Sustainability, MDPI, vol. 15(17), pages 1-31, August.
  1020. Xin Guo & Charles-Albert Lehalle & Renyuan Xu, 2022. "Transaction cost analytics for corporate bonds," Quantitative Finance, Taylor & Francis Journals, vol. 22(7), pages 1295-1319, July.
  1021. Wang, Qin & Yin, Xiangrong, 2008. "A nonlinear multi-dimensional variable selection method for high dimensional data: Sparse MAVE," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4512-4520, May.
  1022. Tomasz Rymarczyk & Krzysztof Król & Edward Kozłowski & Tomasz Wołowiec & Marta Cholewa-Wiktor & Piotr Bednarczuk, 2021. "Application of Electrical Tomography Imaging Using Machine Learning Methods for the Monitoring of Flood Embankments Leaks," Energies, MDPI, vol. 14(23), pages 1-35, December.
  1023. Chung, Won Hee & Gu, Yeong Hyeon & Yoo, Seong Joon, 2022. "District heater load forecasting based on machine learning and parallel CNN-LSTM attention," Energy, Elsevier, vol. 246(C).
  1024. Jenny W Sun & Jessica M Franklin & Kathryn Rough & Rishi J Desai & Sonia Hernández-Díaz & Krista F Huybrechts & Brian T Bateman, 2020. "Predicting overdose among individuals prescribed opioids using routinely collected healthcare utilization data," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-17, October.
  1025. Jiaqi Chen & Michael Tindall, 2016. "The Chen-Tindall system and the lasso operator: improving automatic model performance," Occasional Papers 16-1, Federal Reserve Bank of Dallas.
  1026. Henryk Gurgul & Artur Machno, 2017. "Trade Pattern On Warsaw Stock Exchange And Prediction Of Number Of Trades," Statistics in Transition New Series, Polish Statistical Association, vol. 18(1), pages 91-114, March.
  1027. Ana M. Bianco & Graciela Boente & Gonzalo Chebi, 2022. "Penalized robust estimators in sparse logistic regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(3), pages 563-594, September.
  1028. Ander Wilson & Brian J. Reich, 2014. "Confounder selection via penalized credible regions," Biometrics, The International Biometric Society, vol. 70(4), pages 852-861, December.
  1029. Shengtang Wang & Yingchun Ge, 2022. "Ecological Quality Response to Multi-Scenario Land-Use Changes in the Heihe River Basin," Sustainability, MDPI, vol. 14(5), pages 1-18, February.
  1030. Wang, Dieter & Andrée, Bo Pieter Johannes & Chamorro, Andres Fernando & Spencer, Phoebe Girouard, 2022. "Transitions into and out of food insecurity: A probabilistic approach with panel data evidence from 15 countries," World Development, Elsevier, vol. 159(C).
  1031. Dmitry Kobak & Yves Bernaerts & Marissa A. Weis & Federico Scala & Andreas S. Tolias & Philipp Berens, 2021. "Sparse reduced‐rank regression for exploratory visualisation of paired multivariate data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 980-1000, August.
  1032. Borbáth, Endre & Hutter, Swen, 2020. "Are Political Parties Recapturing the Streets of Europe?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 251-272.
  1033. Bala Rajaratnam & Steven Roberts & Doug Sparks & Onkar Dalal, 2016. "Lasso regression: estimation and shrinkage via the limit of Gibbs sampling," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 153-174, January.
  1034. Sakemoto, Ryuta, 2021. "Economic Evaluation of Cryptocurrency Investment," MPRA Paper 108283, University Library of Munich, Germany.
  1035. Jianing Hou & Shih-Chih Chen & De Xiao, 2018. "Measuring the Benefits of the “One Belt, One Road” Initiative for Manufacturing Industries in China," Sustainability, MDPI, vol. 10(12), pages 1-16, December.
  1036. António Rua & Nuno Lourenço & Francisco Dias, 2018. "Forecasting exports with targeted predictors," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
  1037. Dominique Guegan & Bertrand Hassani, 2017. "Regulatory Learning: how to supervise machine learning models? An application to credit scoring," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01592168, HAL.
  1038. Malefaki, Valia, 2015. "On Flexible Linear Factor Stochastic Volatility Models," MPRA Paper 62216, University Library of Munich, Germany.
  1039. Ghysels, Eric & Qian, Hang, 2019. "Estimating MIDAS regressions via OLS with polynomial parameter profiling," Econometrics and Statistics, Elsevier, vol. 9(C), pages 1-16.
  1040. J. K. Wiencke & Annette M. Molinaro & Gayathri Warrier & Terri Rice & Jennifer Clarke & Jennie W. Taylor & Margaret Wrensch & Helen Hansen & Lucie McCoy & Emily Tang & Stan J. Tamaki & Courtney M. Tam, 2022. "DNA methylation as a pharmacodynamic marker of glucocorticoid response and glioma survival," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
  1041. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2022. "Forecasting European carbon returns using dimension reduction techniques: Commodity versus financial fundamentals," International Journal of Forecasting, Elsevier, vol. 38(3), pages 944-969.
  1042. So-Won Choi & Eul-Bum Lee & Jong-Hyun Kim, 2021. "The Engineering Machine-Learning Automation Platform ( EMAP ): A Big-Data-Driven AI Tool for Contractors’ Sustainable Management Solutions for Plant Projects," Sustainability, MDPI, vol. 13(18), pages 1-33, September.
  1043. Gong, Xue & Ye, Xin & Zhang, Weiguo & Zhang, Yue, 2023. "Predicting energy futures high-frequency volatility using technical indicators: The role of interaction," Energy Economics, Elsevier, vol. 119(C).
  1044. Murat Genç, 2022. "A new double-regularized regression using Liu and lasso regularization," Computational Statistics, Springer, vol. 37(1), pages 159-227, March.
  1045. Fan, Yali & Qin, Guoyou & Zhu, Zhongyi, 2012. "Variable selection in robust regression models for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 109(C), pages 156-167.
  1046. Wang, Jiqian & Guo, Xiaozhu & Tan, Xueping & Chevallier, Julien & Ma, Feng, 2023. "Which exogenous driver is informative in forecasting European carbon volatility: Bond, commodity, stock or uncertainty?," Energy Economics, Elsevier, vol. 117(C).
  1047. Matthew Gentzkow & Bryan T. Kelly & Matt Taddy, 2017. "Text as Data," NBER Working Papers 23276, National Bureau of Economic Research, Inc.
  1048. Niu, Zibo & Liu, Yuanyuan & Gao, Wang & Zhang, Hongwei, 2021. "The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China," Resources Policy, Elsevier, vol. 73(C).
  1049. Jie Ding & Vahid Tarokh & Yuhong Yang, 2018. "Model Selection Techniques -- An Overview," Papers 1810.09583, arXiv.org.
  1050. Bremer, Björn & Hutter, Swen & Kriesi, Hanspeter, 2020. "Electoral Punishment and Protest Politics in Times of Crisis," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 227-250.
  1051. Pei Wang & Shunjie Chen & Sijia Yang, 2022. "Recent Advances on Penalized Regression Models for Biological Data," Mathematics, MDPI, vol. 10(19), pages 1-24, October.
  1052. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2020. "Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States," Working Papers 202058, University of Pretoria, Department of Economics.
  1053. Yuichi Takano & Ryuhei Miyashiro, 2020. "Best subset selection via cross-validation criterion," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 475-488, July.
  1054. James T. E. Chapman & Ajit Desai, 2022. "Macroeconomic Predictions using Payments Data and Machine Learning," Papers 2209.00948, arXiv.org.
  1055. Kawano, Shuichi & Fujisawa, Hironori & Takada, Toyoyuki & Shiroishi, Toshihiko, 2015. "Sparse principal component regression with adaptive loading," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 192-203.
  1056. Xu, Qifa & Zhou, Yingying & Jiang, Cuixia & Yu, Keming & Niu, Xufeng, 2016. "A large CVaR-based portfolio selection model with weight constraints," Economic Modelling, Elsevier, vol. 59(C), pages 436-447.
  1057. Heiss, Florian & Hetzenecker, Stephan & Osterhaus, Maximilian, 2019. "Nonparametric estimation of the random coefficients model: An elastic net approach," Ruhr Economic Papers 824, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  1058. Victor Amelkin & Omid Askarisichani & Young Ji Kim & Thomas W Malone & Ambuj K Singh, 2018. "Dynamics of collective performance in collaboration networks," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-31, October.
  1059. Zhou, Jia & Li, Yang & Zheng, Zemin & Li, Daoji, 2022. "Reproducible learning in large-scale graphical models," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
  1060. Kremer, Philipp J. & Lee, Sangkyun & Bogdan, Małgorzata & Paterlini, Sandra, 2020. "Sparse portfolio selection via the sorted ℓ1-Norm," Journal of Banking & Finance, Elsevier, vol. 110(C).
  1061. Johan Brannlund & Helen Lao & Maureen MacIsaac & Jing Yang, 2023. "Predicting Changes in Canadian Housing Markets with Machine Learning," Discussion Papers 2023-21, Bank of Canada.
  1062. Banholzer, Nicolas & Behrens, Vanessa & Feuerriegel, Stefan & Heinrich, Sebastian & Rammer, Christian & Schmoch, Ulrich & Seliger, Florian & Wörter, Martin, 2019. "Knowledge spillovers from product and process inventions in patents and their impact on firm performance. End report," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 222367.
  1063. Doruk Cengiz & Arindrajit Dube & Attila S. Lindner & David Zentler-Munro, 2021. "Seeing Beyond the Trees: Using Machine Learning to Estimate the Impact of Minimum Wages on Labor Market Outcomes," NBER Working Papers 28399, National Bureau of Economic Research, Inc.
  1064. Hongwei Zhang & Qiang He & Ben Jacobsen & Fuwei Jiang, 2020. "Forecasting stock returns with model uncertainty and parameter instability," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 629-644, August.
  1065. Sungchul Park & Anirban Basu, 2018. "Alternative evaluation metrics for risk adjustment methods," Health Economics, John Wiley & Sons, Ltd., vol. 27(6), pages 984-1010, June.
  1066. Wentao Wang & Jiaxuan Liang & Rong Liu & Yunquan Song & Min Zhang, 2022. "A Robust Variable Selection Method for Sparse Online Regression via the Elastic Net Penalty," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
  1067. Benjamin Ghansah & Ben-Bright Benuwa & Augustine Monney, 2021. "A Discriminative Locality-Sensitive Dictionary Learning With Kernel Weighted KNN Classification for Video Semantic Concepts Analysis," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 17(1), pages 1-24, January.
  1068. Crane-Droesch, Andrew, 2017. "Semiparametric Panel Data Using Neural Networks," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258128, Agricultural and Applied Economics Association.
  1069. Tang, Lu & Zhou, Ling & Song, Peter X.-K., 2020. "Distributed simultaneous inference in generalized linear models via confidence distribution," Journal of Multivariate Analysis, Elsevier, vol. 176(C).
  1070. Wen Wei Loh & Beatrijs Moerkerke & Tom Loeys & Stijn Vansteelandt, 2022. "Nonlinear mediation analysis with high‐dimensional mediators whose causal structure is unknown," Biometrics, The International Biometric Society, vol. 78(1), pages 46-59, March.
  1071. David Degras, 2021. "Sparse group fused lasso for model segmentation: a hybrid approach," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(3), pages 625-671, September.
  1072. Kim Ristolainen, 2022. "Narrative Triggers of Information Sensitivity," Discussion Papers 156, Aboa Centre for Economics.
  1073. Iksoo Huh & Isabel Mendizabal & Taesung Park & Soojin V Yi, 2018. "Functional conservation of sequence determinants at rapidly evolving regulatory regions across mammals," PLOS Computational Biology, Public Library of Science, vol. 14(10), pages 1-21, October.
  1074. Igor Dubnov & Alexander Merkov & Vladimir Arlazarov & Ilia Nikolaev, 2016. "Evidence Maximization Technique for Training of Elastic Nets," Journal of Optimization, Hindawi, vol. 2016, pages 1-7, June.
  1075. Stefano Monni, 2014. "Bayesian variable selection for correlated covariates via colored cliques," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(2), pages 143-163, April.
  1076. Mohammad Arashi & Mina Norouzirad & S. Ejaz Ahmed & Bahadır Yüzbaşı, 2018. "Rank-based Liu regression," Computational Statistics, Springer, vol. 33(3), pages 1525-1561, September.
  1077. Ron Ammar & Pitchumani Sivakumar & Gabor Jarai & John Ryan Thompson, 2019. "A robust data-driven genomic signature for idiopathic pulmonary fibrosis with applications for translational model selection," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-15, April.
  1078. Ahmed R. M. Alsayed, 2023. "Turkish Stock Market from Pandemic to Russian Invasion, Evidence from Developed Machine Learning Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 1107-1123, October.
  1079. Merve Kayacı Çodur, 2023. "Ensemble Machine Learning Approaches for Prediction of Türkiye’s Energy Demand," Energies, MDPI, vol. 17(1), pages 1-25, December.
  1080. Xifen Huang & Jinfeng Xu & Yunpeng Zhou, 2022. "Profile and Non-Profile MM Modeling of Cluster Failure Time and Analysis of ADNI Data," Mathematics, MDPI, vol. 10(4), pages 1-21, February.
  1081. Liming Wang & Xingxiang Li & Xiaoqing Wang & Peng Lai, 2022. "Unified mean-variance feature screening for ultrahigh-dimensional regression," Computational Statistics, Springer, vol. 37(4), pages 1887-1918, September.
  1082. Carmen C. Rodríguez-Martínez & Mitzi Cubilla-Montilla & Purificación Vicente-Galindo & Purificación Galindo-Villardón, 2021. "Sparse STATIS-Dual via Elastic Net," Mathematics, MDPI, vol. 9(17), pages 1-15, August.
  1083. Hong J Kan & Hadi Kharrazi & Hsien-Yen Chang & Dave Bodycombe & Klaus Lemke & Jonathan P Weiner, 2019. "Exploring the use of machine learning for risk adjustment: A comparison of standard and penalized linear regression models in predicting health care costs in older adults," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-13, March.
  1084. Catherine D'Hondt & Rudy De Winne & Eric Ghysels & Steve Raymond, 2019. "Artificial Intelligence Alter Egos: Who benefits from Robo-investing?," Papers 1907.03370, arXiv.org.
  1085. A. Jiran Meitei & Akanksha Saini & Bibhuti Bhusan Mohapatra & Kh. Jitenkumar Singh, 2022. "Predicting child anaemia in the North-Eastern states of India: a machine learning approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(6), pages 2949-2962, December.
  1086. Elizabeth Sanchez & David R Price & Kuei-Pin Chung & Clara Oromendia & Augustine M K Choi & Edward J Schenck & Ilias I Siempos, 2020. "Persistent severe acute respiratory distress syndrome for the prognostic enrichment of trials," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-11, January.
  1087. Lasse Bork & Stig V. Møller & Thomas Q. Pedersen, 2020. "A New Index of Housing Sentiment," Management Science, INFORMS, vol. 66(4), pages 1563-1583, April.
  1088. Wolfgang Karl Härdle & Dedy Dwi Prastyo, 2013. "Default Risk Calculation based on Predictor Selection for the Southeast Asian Industry," SFB 649 Discussion Papers SFB649DP2013-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  1089. Daniel M. Percival & Donald B. Percival & Donald W. Denbo & Edison Gica & Paul Y. Huang & Harold O. Mofjeld & Michael C. Spillane, 2014. "Automated Tsunami Source Modeling Using the Sweeping Window Positive Elastic Net," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 491-499, June.
  1090. Gelper, Sarah & Wilms, Ines & Croux, Christophe, 2016. "Identifying Demand Effects in a Large Network of Product Categories," Journal of Retailing, Elsevier, vol. 92(1), pages 25-39.
  1091. Wang, Tao & Zhu, Lixing, 2011. "Consistent tuning parameter selection in high dimensional sparse linear regression," Journal of Multivariate Analysis, Elsevier, vol. 102(7), pages 1141-1151, August.
  1092. Leandro C. Hermida & E. Michael Gertz & Eytan Ruppin, 2022. "Predicting cancer prognosis and drug response from the tumor microbiome," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
  1093. Bonnier, Jean-Baptiste, 2022. "Forecasting crude oil volatility with exogenous predictors: As good as it GETS?," Energy Economics, Elsevier, vol. 111(C).
  1094. Daniel Ambach & Carsten Croonenbroeck, 2016. "Space-time short- to medium-term wind speed forecasting," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 5-20, March.
  1095. Oliver J. Rutz & Garrett P. Sonnier, 2019. "VANISH regularization for generalized linear models," Quantitative Marketing and Economics (QME), Springer, vol. 17(4), pages 415-437, December.
  1096. Jin, Daxiang & He, Mengxi & Xing, Lu & Zhang, Yaojie, 2022. "Forecasting China's crude oil futures volatility: How to dig out the information of other energy futures volatilities?," Resources Policy, Elsevier, vol. 78(C).
  1097. Zeyu Bian & Erica E. M. Moodie & Susan M. Shortreed & Sahir Bhatnagar, 2023. "Variable selection in regression‐based estimation of dynamic treatment regimes," Biometrics, The International Biometric Society, vol. 79(2), pages 988-999, June.
  1098. C. Davino & R. Romano & D. Vistocco, 2022. "Handling multicollinearity in quantile regression through the use of principal component regression," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 153-174, August.
  1099. Lu Xia & Bin Nan & Yi Li, 2023. "Debiased lasso for generalized linear models with a diverging number of covariates," Biometrics, The International Biometric Society, vol. 79(1), pages 344-357, March.
  1100. Subharup Guha & Rex Jung & David Dunson, 2022. "Predicting phenotypes from brain connection structure," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 639-668, June.
  1101. Pubudu L. W. Jayasekara & Andrew C. Pangia & Margaret M. Wiecek, 2023. "On solving parametric multiobjective quadratic programs with parameters in general locations," Annals of Operations Research, Springer, vol. 320(1), pages 123-172, January.
  1102. Yuan Jiang & Yunxiao He & Heping Zhang, 2016. "Variable Selection With Prior Information for Generalized Linear Models via the Prior LASSO Method," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 355-376, March.
  1103. Lago, Jesus & De Ridder, Fjo & De Schutter, Bart, 2018. "Forecasting spot electricity prices: Deep learning approaches and empirical comparison of traditional algorithms," Applied Energy, Elsevier, vol. 221(C), pages 386-405.
  1104. Cheng, Mingmian & Swanson, Norman R. & Yang, Xiye, 2021. "Forecasting volatility using double shrinkage methods," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 46-61.
  1105. Zanhua Yin, 2020. "Variable selection for sparse logistic regression," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(7), pages 821-836, October.
  1106. Enis Kayış & Taghi Khaniyev & Jaap Suermondt & Karl Sylvester, 2015. "A robust estimation model for surgery durations with temporal, operational, and surgery team effects," Health Care Management Science, Springer, vol. 18(3), pages 222-233, September.
  1107. Bingzhen Chen & Wenjuan Zhai & Lingchen Kong, 2022. "Variable selection and collinearity processing for multivariate data via row-elastic-net regularization," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(1), pages 79-96, March.
  1108. Satre-Meloy, Aven & Diakonova, Marina & Grünewald, Philipp, 2020. "Cluster analysis and prediction of residential peak demand profiles using occupant activity data," Applied Energy, Elsevier, vol. 260(C).
  1109. Philip D. Waggoner & Alec Macmillen, 2022. "Pursuing open-source development of predictive algorithms: the case of criminal sentencing algorithms," Journal of Computational Social Science, Springer, vol. 5(1), pages 89-109, May.
  1110. Mitzi Cubilla-Montilla & Ana Belén Nieto-Librero & M. Purificación Galindo-Villardón & Carlos A. Torres-Cubilla, 2021. "Sparse HJ Biplot: A New Methodology via Elastic Net," Mathematics, MDPI, vol. 9(11), pages 1-15, June.
  1111. Schroeders, Ulrich & Watrin, Luc & Wilhelm, Oliver, 2021. "Age-related nuances in knowledge assessment," Intelligence, Elsevier, vol. 85(C).
  1112. Peter Martey Addo & Dominique Guegan & Bertrand Hassani, 2018. "Credit Risk Analysis using Machine and Deep Learning models," Post-Print halshs-01719983, HAL.
  1113. Jireh Yi-Le Chan & Steven Mun Hong Leow & Khean Thye Bea & Wai Khuen Cheng & Seuk Wai Phoong & Zeng-Wei Hong & Yen-Lin Chen, 2022. "Mitigating the Multicollinearity Problem and Its Machine Learning Approach: A Review," Mathematics, MDPI, vol. 10(8), pages 1-17, April.
  1114. Raymond Salvador & Joaquim Radua & Erick J Canales-Rodríguez & Aleix Solanes & Salvador Sarró & José M Goikolea & Alicia Valiente & Gemma C Monté & María del Carmen Natividad & Amalia Guerrero-Pedraza, 2017. "Evaluation of machine learning algorithms and structural features for optimal MRI-based diagnostic prediction in psychosis," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-24, April.
  1115. Chen, Ding & Guo, Biao & Zhou, Guofu, 2023. "Firm fundamentals and the cross-section of implied volatility shapes," Journal of Financial Markets, Elsevier, vol. 63(C).
  1116. Wang, Yixiu & Zhu, Jiangong & Cao, Liang & Gopaluni, Bhushan & Cao, Yankai, 2023. "Long Short-Term Memory Network with Transfer Learning for Lithium-ion Battery Capacity Fade and Cycle Life Prediction," Applied Energy, Elsevier, vol. 350(C).
  1117. Lee, Youngjo & Oh, Hee-Seok, 2014. "A new sparse variable selection via random-effect model," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 89-99.
  1118. Zhuohui Yu & Shiping Mao & Qingning Lin, 2022. "Has China’s Carbon Emissions Trading Pilot Policy Improved Agricultural Green Total Factor Productivity?," Agriculture, MDPI, vol. 12(9), pages 1-21, September.
  1119. Chen, Shi & Härdle, Wolfgang Karl & López Cabrera, Brenda, 2018. "Regularization Approach for Network Modeling of German Energy Market," IRTG 1792 Discussion Papers 2018-017, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  1120. Mohamed Ibrahim Assoweh & Stéphane Chrétien & Brahim Tamadazte, 2020. "Spectrally Sparse Tensor Reconstruction in Optical Coherence Tomography Using Nuclear Norm Penalisation," Mathematics, MDPI, vol. 8(4), pages 1-31, April.
  1121. Liao Zhu, 2021. "The Adaptive Multi-Factor Model and the Financial Market," Papers 2107.14410, arXiv.org, revised Aug 2021.
  1122. Tao Li & Xudong Liu & Shihan Su, 2018. "Semi-supervised Text Regression with Conditional Generative Adversarial Networks," Papers 1810.01165, arXiv.org, revised Nov 2018.
  1123. Liye Wang & Chong-Yaw Wee & Heung-Il Suk & Xiaoying Tang & Dinggang Shen, 2015. "MRI-Based Intelligence Quotient (IQ) Estimation with Sparse Learning," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-17, March.
  1124. Huiwen Wang & Ruiping Liu & Shanshan Wang & Zhichao Wang & Gilbert Saporta, 2020. "Ultra-high dimensional variable screening via Gram–Schmidt orthogonalization," Computational Statistics, Springer, vol. 35(3), pages 1153-1170, September.
  1125. Ando, Tomohiro & Sueishi, Naoya, 2019. "Regularization parameter selection for penalized empirical likelihood estimator," Economics Letters, Elsevier, vol. 178(C), pages 1-4.
  1126. Philip Kostov & Thankom Arun & Samuel Annim, 2014. "Financial Services to the Unbanked: the case of the Mzansi intervention in South Africa," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 8(2), June.
  1127. Jiang, He & Tao, Changqi & Dong, Yao & Xiong, Ren, 2021. "Robust low-rank multiple kernel learning with compound regularization," European Journal of Operational Research, Elsevier, vol. 295(2), pages 634-647.
  1128. Aggarwal, S.K. & Saini, L.M., 2014. "Solar energy prediction using linear and non-linear regularization models: A study on AMS (American Meteorological Society) 2013–14 Solar Energy Prediction Contest," Energy, Elsevier, vol. 78(C), pages 247-256.
  1129. Sunkyung Kim & Wei Pan & Xiaotong Shen, 2013. "Network-Based Penalized Regression With Application to Genomic Data," Biometrics, The International Biometric Society, vol. 69(3), pages 582-593, September.
  1130. Priscila Espinosa & Jose M. Pavía, 2023. "Automation in Regional Economic Synthetic Index Construction with Uncertainty Measurement," Forecasting, MDPI, vol. 5(2), pages 1-19, April.
  1131. Francesco Curreri & Giacomo Fiumara & Maria Gabriella Xibilia, 2020. "Input Selection Methods for Soft Sensor Design: A Survey," Future Internet, MDPI, vol. 12(6), pages 1-24, June.
  1132. Shuichi Kawano, 2021. "Sparse principal component regression via singular value decomposition approach," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(3), pages 795-823, September.
  1133. Sakae Oya, 2022. "A Bayesian Graphical Approach for Large-Scale Portfolio Management with Fewer Historical Data," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(3), pages 507-526, September.
  1134. Bulligan, Guido & Marcellino, Massimiliano & Venditti, Fabrizio, 2015. "Forecasting economic activity with targeted predictors," International Journal of Forecasting, Elsevier, vol. 31(1), pages 188-206.
  1135. Ma, Shaohui & Fildes, Robert & Huang, Tao, 2016. "Demand forecasting with high dimensional data: The case of SKU retail sales forecasting with intra- and inter-category promotional information," European Journal of Operational Research, Elsevier, vol. 249(1), pages 245-257.
  1136. Rosember Guerra-Urzola & Katrijn Van Deun & Juan C. Vera & Klaas Sijtsma, 2021. "A Guide for Sparse PCA: Model Comparison and Applications," Psychometrika, Springer;The Psychometric Society, vol. 86(4), pages 893-919, December.
  1137. Benjamin Poignard, 2020. "Asymptotic theory of the adaptive Sparse Group Lasso," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(1), pages 297-328, February.
  1138. Julia Gilhodes & Florence Dalenc & Jocelyn Gal & Christophe Zemmour & Eve Leconte & Jean Marie Boher & Thomas Filleron, 2020. "Comparison of Variable Selection Methods for Time-to-Event Data in High-Dimensional Settings," Post-Print hal-02934793, HAL.
  1139. David A Knowles & Gina Bouchard & Sylvia Plevritis, 2019. "Sparse discriminative latent characteristics for predicting cancer drug sensitivity from genomic features," PLOS Computational Biology, Public Library of Science, vol. 15(5), pages 1-18, May.
  1140. Erik Christian Montes Schütte, 2018. "In Search of a Job: Forecasting Employment Growth in the US using Google Trends," CREATES Research Papers 2018-25, Department of Economics and Business Economics, Aarhus University.
  1141. George Kapetanios & Fotis Papailias, 2022. "An Evaluation Framework for Targeted Indicators Aggregates vs. Disaggregates," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-17, Economic Statistics Centre of Excellence (ESCoE).
  1142. Nerilee Hing & Matthew Browne & Alex M T Russell & Matthew Rockloff & Vijay Rawat & Fiona Nicoll & Garry Smith, 2019. "Avoiding gambling harm: An evidence-based set of safe gambling practices for consumers," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-18, October.
  1143. Feraud, Baptiste & Munaut, Carine & Martin, Manon & Verleysen, Michel & Govaerts, Bernadette, 2017. "Combining strong sparsity and competitive predictive power with the L-sOPLS approach for biomarker discovery in metabolomics," LIDAM Discussion Papers ISBA 2017020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  1144. Baragatti, M. & Pommeret, D., 2012. "A study of variable selection using g-prior distribution with ridge parameter," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1920-1934.
  1145. Haibin Zhang & Juan Wei & Meixia Li & Jie Zhou & Miantao Chao, 2014. "On proximal gradient method for the convex problems regularized with the group reproducing kernel norm," Journal of Global Optimization, Springer, vol. 58(1), pages 169-188, January.
  1146. Delen, Dursun & Topuz, Kazim & Eryarsoy, Enes, 2020. "Development of a Bayesian Belief Network-based DSS for predicting and understanding freshmen student attrition," European Journal of Operational Research, Elsevier, vol. 281(3), pages 575-587.
  1147. Kshitij Khare & Malay Ghosh, 2022. "MCMC Convergence for Global-Local Shrinkage Priors," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 211-234, September.
  1148. Tan, Xilong & Tao, Yubo, 2023. "Trend-based forecast of cryptocurrency returns," Economic Modelling, Elsevier, vol. 124(C).
  1149. Joseph Antonelli & Matthew Cefalu & Nathan Palmer & Denis Agniel, 2018. "Doubly robust matching estimators for high dimensional confounding adjustment," Biometrics, The International Biometric Society, vol. 74(4), pages 1171-1179, December.
  1150. Chalise, Prabhakar & Fridley, Brooke L., 2012. "Comparison of penalty functions for sparse canonical correlation analysis," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 245-254.
  1151. Lixin Shen & Bruce W. Suter & Erin E. Tripp, 2019. "Structured Sparsity Promoting Functions," Journal of Optimization Theory and Applications, Springer, vol. 183(2), pages 386-421, November.
  1152. Rajaram Gana, 2022. "Ridge Regression and the Elastic Net: How Do They Do as Finders of True Regressors and Their Coefficients?," Mathematics, MDPI, vol. 10(17), pages 1-27, August.
  1153. Irina Matijosaitiene & Anthony McDowald & Vishal Juneja, 2019. "Predicting Safe Parking Spaces: A Machine Learning Approach to Geospatial Urban and Crime Data," Sustainability, MDPI, vol. 11(10), pages 1-15, May.
  1154. Howard D. Bondell & Brian J. Reich, 2009. "Simultaneous Factor Selection and Collapsing Levels in ANOVA," Biometrics, The International Biometric Society, vol. 65(1), pages 169-177, March.
  1155. Simone Tonini & Francesca Chiaromonte & Alessandro Giovannelli, 2022. "On the impact of serial dependence on penalized regression methods," LEM Papers Series 2022/21, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  1156. Chun-Xia Zhang & Guan-Wei Wang & Jun-Min Liu, 2015. "RandGA: injecting randomness into parallel genetic algorithm for variable selection," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 630-647, March.
  1157. Justin B. Post & Howard D. Bondell, 2013. "Factor Selection and Structural Identification in the Interaction ANOVA Model," Biometrics, The International Biometric Society, vol. 69(1), pages 70-79, March.
  1158. Periklis Gogas & Theophilos Papadimitriou & Emmanouil Sofianos, 2022. "Forecasting unemployment in the euro area with machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 551-566, April.
  1159. Ertefaie Ashkan & Asgharian Masoud & Stephens David A., 2018. "Variable Selection in Causal Inference using a Simultaneous Penalization Method," Journal of Causal Inference, De Gruyter, vol. 6(1), pages 1-16, March.
  1160. Kawano, Shuichi & Fujisawa, Hironori & Takada, Toyoyuki & Shiroishi, Toshihiko, 2018. "Sparse principal component regression for generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 124(C), pages 180-196.
  1161. Howard D. Bondell & Arun Krishna & Sujit K. Ghosh, 2010. "Joint Variable Selection for Fixed and Random Effects in Linear Mixed-Effects Models," Biometrics, The International Biometric Society, vol. 66(4), pages 1069-1077, December.
  1162. Ian C McDowell & Dinesh Manandhar & Christopher M Vockley & Amy K Schmid & Timothy E Reddy & Barbara E Engelhardt, 2018. "Clustering gene expression time series data using an infinite Gaussian process mixture model," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-27, January.
  1163. Abhijeet R Patil & Sangjin Kim, 2020. "Combination of Ensembles of Regularized Regression Models with Resampling-Based Lasso Feature Selection in High Dimensional Data," Mathematics, MDPI, vol. 8(1), pages 1-23, January.
  1164. Xuan Liu & Jianbao Chen, 2021. "Variable Selection for the Spatial Autoregressive Model with Autoregressive Disturbances," Mathematics, MDPI, vol. 9(12), pages 1-20, June.
  1165. She, Yiyuan, 2012. "An iterative algorithm for fitting nonconvex penalized generalized linear models with grouped predictors," Computational Statistics & Data Analysis, Elsevier, vol. 56(10), pages 2976-2990.
  1166. Cui, Hailong & Rajagopalan, Sampath & Ward, Amy R., 2020. "Predicting product return volume using machine learning methods," European Journal of Operational Research, Elsevier, vol. 281(3), pages 612-627.
  1167. Borup, Daniel & Rapach, David E. & Schütte, Erik Christian Montes, 2023. "Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1122-1144.
  1168. Javier Cortes Orihuela & Juan D. Díaz & Pablo Gutiérrez Cubillos & Pablo A. Troncoso, 2024. "Everything’s not lost: revisiting TSTSLS estimates of intergenerational mobility in developing countries," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 31(1), pages 66-94, February.
  1169. Adam Ciarleglio & Eva Petkova & Todd Ogden & Thaddeus Tarpey, 2018. "Constructing treatment decision rules based on scalar and functional predictors when moderators of treatment effect are unknown," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1331-1356, November.
  1170. Marton Gosztonyi, 2023. "Comparative Analysis of X-Y-Z Generation Entrepreneurs in a Semi-Peripheral EU Member Country: Insights from Regularized Regression Techniques," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 191-217.
  1171. Michael Schomaker, 2012. "Shrinkage averaging estimation," Statistical Papers, Springer, vol. 53(4), pages 1015-1034, November.
  1172. Lexin Li & Xiangrong Yin, 2008. "Sliced Inverse Regression with Regularizations," Biometrics, The International Biometric Society, vol. 64(1), pages 124-131, March.
  1173. Silvia Peracchi, 2023. "Migration Crisis in the Local News: Evidence from the French-Italian Border," LIDAM Discussion Papers IRES 2023021, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  1174. Gómez-Orellana, A.M. & Guijo-Rubio, D. & Gutiérrez, P.A. & Hervás-Martínez, C., 2022. "Simultaneous short-term significant wave height and energy flux prediction using zonal multi-task evolutionary artificial neural networks," Renewable Energy, Elsevier, vol. 184(C), pages 975-989.
  1175. Peiran Yu & Ting Kei Pong, 2019. "Iteratively reweighted $$\ell _1$$ ℓ 1 algorithms with extrapolation," Computational Optimization and Applications, Springer, vol. 73(2), pages 353-386, June.
  1176. Shinya Suzuki & Takeshi Yamashita & Tsuyoshi Sakama & Takuto Arita & Naoharu Yagi & Takayuki Otsuka & Hiroaki Semba & Hiroto Kano & Shunsuke Matsuno & Yuko Kato & Tokuhisa Uejima & Yuji Oikawa & Minor, 2019. "Comparison of risk models for mortality and cardiovascular events between machine learning and conventional logistic regression analysis," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-14, September.
  1177. Osamu Komori & Shinto Eguchi & John B. Copas, 2015. "Generalized t-statistic for two-group classification," Biometrics, The International Biometric Society, vol. 71(2), pages 404-416, June.
  1178. Dominique Guegan & Bertrand Hassani, 2017. "Regulatory Learning: how to supervise machine learning models? An application to credit scoring," Post-Print halshs-01592168, HAL.
  1179. Jack Dunn & Ying Daisy Zhuo, 2022. "Detecting Racial Bias in Jury Selection," SN Operations Research Forum, Springer, vol. 3(3), pages 1-17, September.
  1180. Kristen M Brown & Ana V Diez-Roux & Jennifer A Smith & Belinda L Needham & Bhramar Mukherjee & Erin B Ware & Yongmei Liu & Steven W Cole & Teresa E Seeman & Sharon L R Kardia, 2019. "Expression of socially sensitive genes: The multi-ethnic study of atherosclerosis," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-15, April.
  1181. Hirose, Kei & Tateishi, Shohei & Konishi, Sadanori, 2013. "Tuning parameter selection in sparse regression modeling," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 28-40.
  1182. Zhou, Jingke & Zhu, Lixing, 2016. "Principal minimax support vector machine for sufficient dimension reduction with contaminated data," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 33-48.
  1183. Jian Huang & Yuling Jiao & Lican Kang & Jin Liu & Yanyan Liu & Xiliang Lu, 2022. "GSDAR: a fast Newton algorithm for $$\ell _0$$ ℓ 0 regularized generalized linear models with statistical guarantee," Computational Statistics, Springer, vol. 37(1), pages 507-533, March.
  1184. Ismaila Baldé & Yi Archer Yang & Geneviève Lefebvre, 2023. "Reader reaction to “Outcome‐adaptive lasso: Variable selection for causal inference” by Shortreed and Ertefaie (2017)," Biometrics, The International Biometric Society, vol. 79(1), pages 514-520, March.
  1185. Anshul Verma & Riccardo Junior Buonocore & Tiziana di Matteo, 2017. "A cluster driven log-volatility factor model: a deepening on the source of the volatility clustering," Papers 1712.02138, arXiv.org, revised May 2018.
  1186. Luigi Biagini & Simone Severini, 2021. "The role of Common Agricultural Policy (CAP) in enhancing and stabilising farm income: an analysis of income transfer efficiency and the Income Stabilisation Tool," Papers 2104.14188, arXiv.org.
  1187. Ya Chen & Mike Tsionas & Valentin Zelenyuk, 2020. "LASSO DEA for small and big data," CEPA Working Papers Series WP092020, School of Economics, University of Queensland, Australia.
  1188. Duras, Toni & Javed, Farrukh & Månsson, Kristofer & Sjölander, Pär & Söderberg, Magnus, 2023. "Using machine learning to select variables in data envelopment analysis: Simulations and application using electricity distribution data," Energy Economics, Elsevier, vol. 120(C).
  1189. Gambella, Claudio & Ghaddar, Bissan & Naoum-Sawaya, Joe, 2021. "Optimization problems for machine learning: A survey," European Journal of Operational Research, Elsevier, vol. 290(3), pages 807-828.
  1190. Yao, Weixin & Wang, Qin, 2013. "Robust variable selection through MAVE," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 42-49.
  1191. Ksenia Mayorova & Nikita Fokin, 2021. "Nowcasting Growth Rates of Russia’s Export and Import by Commodity Group," Russian Journal of Money and Finance, Bank of Russia, vol. 80(3), pages 34-48, September.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.