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Regularization and variable selection via the elastic net

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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. Angélica Pigola & Bruno Fischer & Gustavo Hermínio Salati Marcondes de Moraes, 2024. "Impacts of Digital Entrepreneurial Ecosystems on Sustainable Development: Insights from Latin America," Sustainability, MDPI, vol. 16(18), pages 1-30, September.
  4. Brian Chi-ang Lin & Siqi Zheng & 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. Özen, Kadir & Yıldırım, Dilem, 2021. "Application of bagging in day-ahead electricity price forecasting and factor augmentation," Energy Economics, Elsevier, vol. 103(C).
  6. 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.
  7. 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.
  8. Oxana Babecka Kucharcukova & Jan Bruha, 2016. "Nowcasting the Czech Trade Balance," Working Papers 2016/11, Czech National Bank.
  9. 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.
  10. 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.
  11. Wenjia Wang & Yi-Hui Zhou, 2022. "A Double Penalty Model for Ensemble Learning," Mathematics, MDPI, vol. 10(23), pages 1-23, November.
  12. 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.
  13. 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.
  14. Freire, Gustavo, 2021. "Tail risk and investors’ concerns: Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
  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. 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.
  17. 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.
  18. Cepni, Oguzhan & Clements, Michael P., 2024. "How local is the local inflation factor? Evidence from emerging European countries," International Journal of Forecasting, Elsevier, vol. 40(1), pages 160-183.
  19. 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.
  20. Kockerols, Thore & Kok, Christoffer, 2019. "Leaning against the wind: macroprudential policy and the financial cycle," Working Paper Series 2223, European Central Bank.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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).
  26. 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.
  27. 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.
  28. 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.
  29. Liang, Chong & Schienle, Melanie, 2019. "Determination of vector error correction models in high dimensions," Journal of Econometrics, Elsevier, vol. 208(2), pages 418-441.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. 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.
  35. 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.
  36. 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.
  37. 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.
  38. 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.
  39. 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.
  40. 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.
  41. 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.
  42. 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.
  43. Miyazaki, Izuru, 2023. "Recovery of partly sparse and dense signals," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
  44. 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.
  45. 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.
  46. 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).
  47. 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.
  48. 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.
  49. Narajewski, Michał & Ziel, Florian, 2020. "Econometric modelling and forecasting of intraday electricity prices," Journal of Commodity Markets, Elsevier, vol. 19(C).
  50. 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.
  51. 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.
  52. 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.
  53. 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.
  54. 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.
  55. 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.
  56. 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.
  57. Indrawan Nugrahanto & Hariyanto Gunawan & Hsing-Yu Chen, 2024. "Innovative Approaches to Sustainable Computer Numeric Control Machining: A Machine Learning Perspective on Energy Efficiency," Sustainability, MDPI, vol. 16(9), pages 1-22, April.
  58. 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.
  59. 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.
  60. 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.
  61. 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.
  62. 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.
  63. Bai, Jushan & Ng, Serena, 2008. "Forecasting economic time series using targeted predictors," Journal of Econometrics, Elsevier, vol. 146(2), pages 304-317, October.
  64. Robert Chen & Áine Duffy & Ben O. Petrazzini & Ha My Vy & David Stein & Matthew Mort & Joshua K. Park & Avner Schlessinger & Yuval Itan & David N. Cooper & Daniel M. Jordan & Ghislain Rocheleau & Ron , 2024. "Expanding drug targets for 112 chronic diseases using a machine learning-assisted genetic priority score," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
  65. 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.
  66. Fan, Jianqing & Ke, Yuan & Wang, Kaizheng, 2020. "Factor-adjusted regularized model selection," Journal of Econometrics, Elsevier, vol. 216(1), pages 71-85.
  67. Qiu, Yue & Zheng, Yuchen, 2023. "Improving box office projections through sentiment analysis: Insights from regularization-based forecast combinations," Economic Modelling, Elsevier, vol. 125(C).
  68. 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.
  69. 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).
  70. 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.
  71. 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.
  72. 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.
  73. Adam N. Smith & Stephan Seiler & Ishant Aggarwal, 2023. "Optimal Price Targeting," Marketing Science, INFORMS, vol. 42(3), pages 476-499, May.
  74. 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.
  75. 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.
  76. 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.
  77. 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.
  78. 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.
  79. 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.
  80. 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.
  81. 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.
  82. 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.
  83. 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).
  84. Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2023. "A Machine Learning Approach to Volatility Forecasting," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1680-1727.
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  86. repec:dau:papers:123456789/10079 is not listed on IDEAS
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  90. 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).
  91. Stig Vinther Møller & Thomas Pedersen & Erik Christian Montes Schütte & Allan Timmermann, 2024. "Search and Predictability of Prices in the Housing Market," Management Science, INFORMS, vol. 70(1), pages 415-438, January.
  92. Shi, Guiling & Lim, Chae Young & Maiti, Tapabrata, 2019. "Model selection using mass-nonlocal prior," Statistics & Probability Letters, Elsevier, vol. 147(C), pages 36-44.
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  94. 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.
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  104. Sebri, Maamar & Dachraoui, Hajer, 2021. "Natural resources and income inequality: A meta-analytic review," Resources Policy, Elsevier, vol. 74(C).
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  106. 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.
  107. 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.
  108. 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.
  109. 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.
  110. 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.
  111. 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.
  112. 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.
  113. 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.
  114. 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.
  115. 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.
  116. 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.
  117. 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.
  118. Lim Hao Shen Keith, 2024. "Covariance Matrix Analysis for Optimal Portfolio Selection," Papers 2407.08748, arXiv.org.
  119. 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.
  120. Yang, Yuan & McMahan, Christopher S. & Wang, Yu-Bo & Ouyang, Yuyuan, 2024. "Estimation of l0 norm penalized models: A statistical treatment," Computational Statistics & Data Analysis, Elsevier, vol. 192(C).
  121. 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.
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  1264. 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.
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