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Extended Bayesian information criteria for model selection with large model spaces

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Cited by:

  1. Zhao, Xin & Zhang, Jingru & Lin, Wei, 2023. "Clustering multivariate count data via Dirichlet-multinomial network fusion," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
  2. Elena Geminiani & Giampiero Marra & Irini Moustaki, 2021. "Single- and Multiple-Group Penalized Factor Analysis: A Trust-Region Algorithm Approach with Integrated Automatic Multiple Tuning Parameter Selection," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 65-95, March.
  3. Rahul Ghosal & Arnab Maity & Timothy Clark & Stefano B. Longo, 2020. "Variable selection in functional linear concurrent regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(3), pages 565-587, June.
  4. Chen, J. & Li, D. & Li, Y. & Linton, O. B., 2022. "Estimating Time-Varying Networks for High-Dimensional Time Series," Cambridge Working Papers in Economics 2273, Faculty of Economics, University of Cambridge.
  5. 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.
  6. 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.
  7. Wang, Tao & Zhu, Lixing, 2013. "Sparse sufficient dimension reduction using optimal scoring," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 223-232.
  8. Chen, Jiahui & Wang, Quanquan & Liang, Yiting & Chen, Baitao & Ren, Ping, 2023. "Comorbidity of loneliness and social anxiety in adolescents: Bridge symptoms and peer relationships," Social Science & Medicine, Elsevier, vol. 334(C).
  9. Yingying Fan & Cheng Yong Tang, 2013. "Tuning parameter selection in high dimensional penalized likelihood," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(3), pages 531-552, June.
  10. Fabio Corradi & Monica Musio, 2020. "Causes of effects via a Bayesian model selection procedure," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1777-1792, October.
  11. Yoshida, Takuma & Naito, Kanta, 2019. "Regression with stagewise minimization on risk function," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 123-143.
  12. M. Marsman & K. Huth & L. J. Waldorp & I. Ntzoufras, 2022. "Objective Bayesian Edge Screening and Structure Selection for Ising Networks," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 47-82, March.
  13. Lan Wang & Jianhui Zhou & Annie Qu, 2012. "Penalized Generalized Estimating Equations for High-Dimensional Longitudinal Data Analysis," Biometrics, The International Biometric Society, vol. 68(2), pages 353-360, June.
  14. Neubeck, Markus & Karbach, Julia & Könen, Tanja, 2022. "Network models of cognitive abilities in younger and older adults," Intelligence, Elsevier, vol. 90(C).
  15. Fidèle Sebera & Joao Ricardo Nickenig Vissoci & Josiane Umwiringirwa & Dirk E Teuwen & Paul E Boon & Peter Dedeken, 2020. "Validity, reliability and cut-offs of the Patient Health Questionnaire-9 as a screening tool for depression among patients living with epilepsy in Rwanda," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-16, June.
  16. Frommlet, Florian & Ruhaltinger, Felix & Twaróg, Piotr & Bogdan, Małgorzata, 2012. "Modified versions of Bayesian Information Criterion for genome-wide association studies," Computational Statistics & Data Analysis, Elsevier, vol. 56(5), pages 1038-1051.
  17. 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.
  18. Raja, Akash, 2023. "The impact of changes in bank capital requirements," Bank of England working papers 1004, Bank of England.
  19. Lian, Heng & Kim, Yongdai, 2016. "Nonconvex penalized reduced rank regression and its oracle properties in high dimensions," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 383-393.
  20. Dimitris Korobilis & Kenichi Shimizu, 2022. "Bayesian Approaches to Shrinkage and Sparse Estimation," Foundations and Trends(R) in Econometrics, now publishers, vol. 11(4), pages 230-354, June.
  21. 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.
  22. 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.
  23. Ning Hao & Hao Helen Zhang, 2017. "A Note on High-Dimensional Linear Regression With Interactions," The American Statistician, Taylor & Francis Journals, vol. 71(4), pages 291-297, October.
  24. Guo, Xiao & Chen, Yu & Tang, Cheng Yong, 2023. "Information criteria for latent factor models: A study on factor pervasiveness and adaptivity," Journal of Econometrics, Elsevier, vol. 233(1), pages 237-250.
  25. Yundong Tu & Siwei Wang, 2023. "Variable Screening and Model Averaging for Expectile Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 574-598, June.
  26. Zak-Szatkowska, Malgorzata & Bogdan, Malgorzata, 2011. "Modified versions of the Bayesian Information Criterion for sparse Generalized Linear Models," Computational Statistics & Data Analysis, Elsevier, vol. 55(11), pages 2908-2924, November.
  27. Shiqiang Jin & Gyuhyeong Goh, 2021. "Bayesian selection of best subsets via hybrid search," Computational Statistics, Springer, vol. 36(3), pages 1991-2007, September.
  28. Jinyuan Chang & Zhentao Shi & Jia Zhang, 2021. "Culling the herd of moments with penalized empirical likelihood," Papers 2108.03382, arXiv.org, revised May 2022.
  29. Tu, Yundong & Xie, Xinling, 2023. "Penetrating sporadic return predictability," Journal of Econometrics, Elsevier, vol. 237(1).
  30. Xiandeng Jiang & Le Chang & Yanlin Shi, 2023. "Housing price diffusions in mainland China: evidence from a spatially penalized graphical VAR model," Empirical Economics, Springer, vol. 64(2), pages 765-795, February.
  31. Erhardt Vinzenz & Bogdan Malgorzata & Czado Claudia, 2010. "Locating Multiple Interacting Quantitative Trait Loci with the Zero-Inflated Generalized Poisson Regression," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-27, June.
  32. Jia Chen & Degui Li & Yuning Li & Oliver Linton, 2023. "Estimating Time-Varying Networks for High-Dimensional Time Series," Papers 2302.02476, arXiv.org.
  33. Ruggieri, Eric & Lawrence, Charles E., 2012. "On efficient calculations for Bayesian variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1319-1332.
  34. Liu, Jianyu & Yu, Guan & Liu, Yufeng, 2019. "Graph-based sparse linear discriminant analysis for high-dimensional classification," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 250-269.
  35. Claire Giordano, 2021. "How frequent a BEER? Assessing the impact of data frequency on real exchange rate misalignment estimation," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 365-404, July.
  36. 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.
  37. Guo, Jie & Tang, Manlai & Tian, Maozai & Zhu, Kai, 2013. "Variable selection in high-dimensional partially linear additive models for composite quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 65(C), pages 56-67.
  38. Xiaoli Gao, 2018. "A flexible shrinkage operator for fussy grouped variable selection," Statistical Papers, Springer, vol. 59(3), pages 985-1008, September.
  39. Yawei He & Zehua Chen, 2016. "The EBIC and a sequential procedure for feature selection in interactive linear models with high-dimensional data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(1), pages 155-180, February.
  40. Chen, J. & Li, D. & Li, Y. & Linton, O. B., 2022. "Estimating Time-Varying Networks for High-Dimensional Time Series," Janeway Institute Working Papers 2231, Faculty of Economics, University of Cambridge.
  41. Woraphon Yamaka & Xuefeng Zhang & Paravee Maneejuk, 2021. "Analyzing the Influence of Transportations on Chinese Inbound Tourism: Markov Switching Penalized Regression Approaches," Mathematics, MDPI, vol. 9(5), pages 1-23, March.
  42. Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
  43. Kaixu Yang & Tapabrata Maiti, 2022. "Ultrahigh‐dimensional generalized additive model: Unified theory and methods," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 917-942, September.
  44. Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Working Papers 03/2021, IMT School for Advanced Studies Lucca, revised Jul 2021.
  45. Gaorong Li & Liugen Xue & Heng Lian, 2012. "SCAD-penalised generalised additive models with non-polynomial dimensionality," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(3), pages 681-697.
  46. Juliana Ribeiro Francelino Sampaio & Suely Arruda Vidal & Paulo Savio Angeiras de Goes & Paulo Felipe R. Bandeira & José Eulálio Cabral Filho, 2021. "Sociodemographic, Behavioral and Oral Health Factors in Maternal and Child Health: An Interventional and Associative Study from the Network Perspective," IJERPH, MDPI, vol. 18(8), pages 1-13, April.
  47. 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.
  48. 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.
  49. Zhengjia Wang & John Magnotti & Michael S. Beauchamp & Meng Li, 2023. "Functional group bridge for simultaneous regression and support estimation," Biometrics, The International Biometric Society, vol. 79(2), pages 1226-1238, June.
  50. Ryan A. Peterson & Joseph E. Cavanaugh, 2022. "Ranked sparsity: a cogent regularization framework for selecting and estimating feature interactions and polynomials," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(3), pages 427-454, September.
  51. Meichen Dong & Yiping He & Yuchao Jiang & Fei Zou, 2023. "Joint gene network construction by single‐cell RNA sequencing data," Biometrics, The International Biometric Society, vol. 79(2), pages 915-925, June.
  52. 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.
  53. Xiaotong Shen & Wei Pan & Yunzhang Zhu & Hui Zhou, 2013. "On constrained and regularized high-dimensional regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(5), pages 807-832, October.
  54. Ting‐Huei Chen & Hanaa Boughal, 2021. "A penalized structural equation modeling method accounting for secondary phenotypes for variable selection on genetically regulated expression from PrediXcan for Alzheimer's disease," Biometrics, The International Biometric Society, vol. 77(1), pages 362-371, March.
  55. 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).
  56. Xiang Zhang & Yichao Wu & Lan Wang & Runze Li, 2016. "Variable selection for support vector machines in moderately high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 53-76, January.
  57. Emre Demirkaya & Yang Feng & Pallavi Basu & Jinchi Lv, 2022. "Large-scale model selection in misspecified generalized linear models [Information theory and an extension of the maximum likelihood principle]," Biometrika, Biometrika Trust, vol. 109(1), pages 123-136.
  58. Lian, Heng & Meng, Jie & Zhao, Kaifeng, 2015. "Spline estimator for simultaneous variable selection and constant coefficient identification in high-dimensional generalized varying-coefficient models," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 81-103.
  59. Yongli Zhang & Xiaotong Shen, 2015. "Adaptive Modeling Procedure Selection by Data Perturbation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 541-551, October.
  60. Zhao, Bangxin & Liu, Xin & He, Wenqing & Yi, Grace Y., 2021. "Dynamic tilted current correlation for high dimensional variable screening," Journal of Multivariate Analysis, Elsevier, vol. 182(C).
  61. Jirak, Moritz, 2014. "Simultaneous confidence bands for sequential autoregressive fitting," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 130-149.
  62. Shan Luo & Zehua Chen, 2014. "Sequential Lasso Cum EBIC for Feature Selection With Ultra-High Dimensional Feature Space," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1229-1240, September.
  63. Monika Trojanová & Alexander Hošovský & Tomáš Čakurda, 2022. "Evaluation of Machine Learning-Based Parsimonious Models for Static Modeling of Fluidic Muscles in Compliant Mechanisms," Mathematics, MDPI, vol. 11(1), pages 1-33, December.
  64. 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.
  65. Yao Dong & He Jiang, 2018. "A Two-Stage Regularization Method for Variable Selection and Forecasting in High-Order Interaction Model," Complexity, Hindawi, vol. 2018, pages 1-12, November.
  66. Lu Tang & Ling Zhou & Peter X. K. Song, 2019. "Fusion learning algorithm to combine partially heterogeneous Cox models," Computational Statistics, Springer, vol. 34(1), pages 395-414, March.
  67. Vera Djordjilović & Monica Chiogna & Chiara Romualdi, 2020. "Simulating gene silencing through intervention analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 887-907, August.
  68. Lian, Heng & Du, Pang & Li, YuanZhang & Liang, Hua, 2014. "Partially linear structure identification in generalized additive models with NP-dimensionality," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 197-208.
  69. Antonio Rodríguez Andrés & Abraham Otero & Voxi Heinrich Amavilah, 2022. "Knowledge economy classification in African countries: A model-based clustering approach," Information Technology for Development, Taylor & Francis Journals, vol. 28(2), pages 372-396, April.
  70. Zhang, Xiaochen & Zhang, Qingzhao & Ma, Shuangge & Fang, Kuangnan, 2022. "Subgroup analysis for high-dimensional functional regression," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
  71. Wang, Kaibo & Yeh, Arthur B. & Li, Bo, 2014. "Simultaneous monitoring of process mean vector and covariance matrix via penalized likelihood estimation," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 206-217.
  72. Mingli Chen & Kengo Kato & Chenlei Leng, 2021. "Analysis of networks via the sparse β‐model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(5), pages 887-910, November.
  73. Liu, Sitian & Su, Yichen, 2022. "The Effect of Working from Home on the Agglomeration Economies of Cities: Evidence from Advertised Wages," MPRA Paper 114429, University Library of Munich, Germany.
  74. Jianyu Liu & Wei Sun & Yufeng Liu, 2019. "Joint skeleton estimation of multiple directed acyclic graphs for heterogeneous population," Biometrics, The International Biometric Society, vol. 75(1), pages 36-47, March.
  75. Lei Wang & Wei Ma, 2021. "Improved empirical likelihood inference and variable selection for generalized linear models with longitudinal nonignorable dropouts," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(3), pages 623-647, June.
  76. Molly C. Klanderman & Kathryn B. Newhart & Tzahi Y. Cath & Amanda S. Hering, 2020. "Fault isolation for a complex decentralized waste water treatment facility," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 931-951, August.
  77. Lian, Heng, 2014. "Semiparametric Bayesian information criterion for model selection in ultra-high dimensional additive models," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 304-310.
  78. Markus Eller & Branimir Jovanovic & Thomas Scheiber, 2021. "Supplement to “What do people in CESEE think about public debt?”," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q3/21.
  79. 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.
  80. Chen, Yunxiao & Li, Xiaoou & Liu, Jingchen & Ying, Zhiliang, 2017. "Regularized latent class analysis with application in cognitive diagnosis," LSE Research Online Documents on Economics 103182, London School of Economics and Political Science, LSE Library.
  81. Chun Wang, 2021. "Using Penalized EM Algorithm to Infer Learning Trajectories in Latent Transition CDM," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 167-189, March.
  82. Campbell Foubister & Esther M F van Sluijs & Anna Vignoles & Paul Wilkinson & Edward C F Wilson & Caroline H D Croxson & Helen Elizabeth Brown & Kirsten Corder, 2021. "The school policy, social, and physical environment and change in adolescent physical activity: An exploratory analysis using the LASSO," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-14, April.
  83. Luke Mosley & Idris A. Eckley & Alex Gibberd, 2022. "Sparse temporal disaggregation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2203-2233, October.
  84. Tang, Yanlin & Song, Xinyuan & Wang, Huixia Judy & Zhu, Zhongyi, 2013. "Variable selection in high-dimensional quantile varying coefficient models," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 115-132.
  85. Eun Ryung Lee & Seyoung Park & Sang Kyu Lee & Hyokyoung G. Hong, 2023. "Quantile forward regression for high-dimensional survival data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(4), pages 769-806, October.
  86. Hu, Yuao & Lian, Heng, 2013. "Variable selection in a partially linear proportional hazards model with a diverging dimensionality," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 61-69.
  87. Yunxiao Chen & Xiaoou Li & Jingchen Liu & Zhiliang Ying, 2018. "Robust Measurement via A Fused Latent and Graphical Item Response Theory Model," Psychometrika, Springer;The Psychometric Society, vol. 83(3), pages 538-562, September.
  88. Pan, Qing & Zhao, Yunpeng, 2016. "Integrative weighted group lasso and generalized local quadratic approximation," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 66-78.
  89. David Rossell & Donatello Telesca, 2017. "Nonlocal Priors for High-Dimensional Estimation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 254-265, January.
  90. Li, Yujie & Li, Gaorong & Lian, Heng & Tong, Tiejun, 2017. "Profile forward regression screening for ultra-high dimensional semiparametric varying coefficient partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 133-150.
  91. Ronaldo Carpio & Meixin Guo, 2021. "Bayesian estimation of the Eurozone currency union effect," Review of International Economics, Wiley Blackwell, vol. 29(3), pages 511-532, August.
  92. Fan, Zhaohu & Reimherr, Matthew, 2017. "High-dimensional adaptive function-on-scalar regression," Econometrics and Statistics, Elsevier, vol. 1(C), pages 167-183.
  93. Yunxiao Chen & Xiaoou Li & Jingchen Liu & Zhiliang Ying, 2017. "Regularized Latent Class Analysis with Application in Cognitive Diagnosis," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 660-692, September.
  94. 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.
  95. Hong, Hyokyoung G. & Zheng, Qi & Li, Yi, 2019. "Forward regression for Cox models with high-dimensional covariates," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 268-290.
  96. Dora Gyori & Bernadett Frida Farkas & Lili Olga Horvath & Daniel Komaromy & Gergely Meszaros & Dora Szentivanyi & Judit Balazs, 2021. "The Association of Nonsuicidal Self-Injury with Quality of Life and Mental Disorders in Clinical Adolescents—A Network Approach," IJERPH, MDPI, vol. 18(4), pages 1-21, February.
  97. repec:jss:jstsof:28:i02 is not listed on IDEAS
  98. Miao Yang & Lan Xue & Lijian Yang, 2016. "Variable selection for additive model via cumulative ratios of empirical strengths total," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(3), pages 595-616, September.
  99. Katayama, Shota & Imori, Shinpei, 2014. "Lasso penalized model selection criteria for high-dimensional multivariate linear regression analysis," Journal of Multivariate Analysis, Elsevier, vol. 132(C), pages 138-150.
  100. 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.
  101. Lian, Heng, 2012. "A note on the consistency of Schwarz’s criterion in linear quantile regression with the SCAD penalty," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1224-1228.
  102. Li, Xinyi & Wang, Li & Nettleton, Dan, 2019. "Sparse model identification and learning for ultra-high-dimensional additive partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 204-228.
  103. Yuyang Liu & Pengfei Pi & Shan Luo, 2023. "A semi-parametric approach to feature selection in high-dimensional linear regression models," Computational Statistics, Springer, vol. 38(2), pages 979-1000, June.
  104. Jones, Benjamin A., 2018. "Forest-attacking Invasive Species and Infant Health: Evidence From the Invasive Emerald Ash Borer," Ecological Economics, Elsevier, vol. 154(C), pages 282-293.
  105. Ma, Yingying & Guo, Shaojun & Wang, Hansheng, 2023. "Sparse spatio-temporal autoregressions by profiling and bagging," Journal of Econometrics, Elsevier, vol. 232(1), pages 132-147.
  106. Agota Fodor & Vincent Segura & Marie Denis & Samuel Neuenschwander & Alexandre Fournier-Level & Philippe Chatelet & Félix Abdel Aziz Homa & Thierry Lacombe & Patrice This & Loic Le Cunff, 2014. "Genome-Wide Prediction Methods in Highly Diverse and Heterozygous Species: Proof-of-Concept through Simulation in Grapevine," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-14, November.
  107. Falco J. Bargagli-Dtoffi & Massimo Riccaboni & Armando Rungi, 2020. "Machine Learning for Zombie Hunting. Firms Failures and Financial Constraints," Working Papers 01/2020, IMT School for Advanced Studies Lucca, revised Jun 2020.
  108. 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.
  109. Juntao Wang & Yuan Li, 2023. "DINA Model with Entropy Penalization," Mathematics, MDPI, vol. 11(18), pages 1-16, September.
  110. Zhaoliang Wang & Liugen Xue & Gaorong Li & Fei Lu, 2019. "Spline estimator for ultra-high dimensional partially linear varying coefficient models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(3), pages 657-677, June.
  111. Shang Wu & Hazel Bateman & Ralph Stevens & Susan Thorp, 2022. "Flexible insurance for long‐term care: A study of stated preferences," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(3), pages 823-858, September.
  112. Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023. "Big data forecasting of South African inflation," Empirical Economics, Springer, vol. 65(1), pages 149-188, July.
  113. Zehua Chen & Yiwei Jiang, 2020. "A two-stage sequential conditional selection approach to sparse high-dimensional multivariate regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(1), pages 65-90, February.
  114. Liu, Jingyuan & Lou, Lejia & Li, Runze, 2018. "Variable selection for partially linear models via partial correlation," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 418-434.
  115. Honda, Toshio & 本田, 敏雄 & Lin, Chien-Tong, 2022. "Forward variable selection for ultra-high dimensional quantile regression models," Discussion Papers 2021-02, Graduate School of Economics, Hitotsubashi University.
  116. Qifan Song & Guang Cheng, 2020. "Bayesian Fusion Estimation via t Shrinkage," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 82(2), pages 353-385, August.
  117. 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).
  118. Yanhang Zhang & Junxian Zhu & Jin Zhu & Xueqin Wang, 2023. "A Splicing Approach to Best Subset of Groups Selection," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 104-119, January.
  119. HONDA, Toshio & 本田, 敏雄 & ING, Ching-Kang & WU, Wei-Ying, 2017. "Adaptively weighted group Lasso for semiparametric quantile regression models," Discussion Papers 2017-04, Graduate School of Economics, Hitotsubashi University.
  120. Sebri, Maamar & Dachraoui, Hajer, 2021. "Natural resources and income inequality: A meta-analytic review," Resources Policy, Elsevier, vol. 74(C).
  121. Chaohui Guo & Hu Yang & Jing Lv, 2017. "Robust variable selection in high-dimensional varying coefficient models based on weighted composite quantile regression," Statistical Papers, Springer, vol. 58(4), pages 1009-1033, December.
  122. Park, Jaewoo & Jin, Ick Hoon & Schweinberger, Michael, 2022. "Bayesian model selection for high-dimensional Ising models, with applications to educational data," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).
  123. 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.
  124. Tae-Hwy Lee & Ekaterina Seregina, 2020. "Learning from Forecast Errors: A New Approach to Forecast Combination," Working Papers 202024, University of California at Riverside, Department of Economics.
  125. Iris Chen & Yogeshwar D Kelkar & Yu Gu & Jie Zhou & Xing Qiu & Hulin Wu, 2017. "High-dimensional linear state space models for dynamic microbial interaction networks," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-20, November.
  126. Lafit, Ginette & Nogales Martín, Francisco Javier, 2017. "Robust and sparse estimation of high-dimensional precision matrices via bivariate outlier detection," DES - Working Papers. Statistics and Econometrics. WS 24534, Universidad Carlos III de Madrid. Departamento de Estadística.
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