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Simultaneous Regression Shrinkage, Variable Selection, and Supervised Clustering of Predictors with OSCAR

Citations

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Cited by:

  1. 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.
  2. 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.
  3. Peter Radchenko & Gourab Mukherjee, 2017. "Convex clustering via l 1 fusion penalization," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1527-1546, November.
  4. Aman Ullah & Xinyu Zhang, 2015. "Grouped Model Averaging for Finite Sample Size," Working Papers 201501, University of California at Riverside, Department of Economics.
  5. 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.
  6. Hou, Zhaohan & Wang, Lei, 2024. "Heterogeneous quantile regression for longitudinal data with subgroup structures," Computational Statistics & Data Analysis, Elsevier, vol. 194(C).
  7. Hiraki, Kazuhiro & Sun, Chuanping, 2022. "A toolkit for exploiting contemporaneous stock correlations," Journal of Empirical Finance, Elsevier, vol. 65(C), pages 99-124.
  8. Özge Sürer & Daniel W. Apley & Edward C. Malthouse, 2024. "Discovering interpretable structure in longitudinal predictors via coefficient trees," 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. 18(4), pages 911-951, December.
  9. 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.
  10. 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.
  11. Cui, Qiurong & Xu, Yuqing & Zhang, Zhengjun & Chan, Vincent, 2021. "Max-linear regression models with regularization," Journal of Econometrics, Elsevier, vol. 222(1), pages 579-600.
  12. Piotr Graczyk & Ulrike Schneider & Tomasz Skalski & Patrick Tardivel, 2026. "A Unified Framework for Pattern Recovery in Penalized and Thresholded Estimation and its Geometry," Journal of Optimization Theory and Applications, Springer, vol. 208(1), pages 1-41, January.
  13. Jen-Chieh Teng & Chin-Tsang Chiang & Alvin Lim, 2024. "An effective method for identifying clusters of robot strengths," Computational Statistics, Springer, vol. 39(6), pages 3303-3345, September.
  14. repec:rim:rimwps:18-11 is not listed on IDEAS
  15. 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.
  16. 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.
  17. 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.
  18. Lu Tang & Peter X.‐K. Song, 2021. "Poststratification fusion learning in longitudinal data analysis," Biometrics, The International Biometric Society, vol. 77(3), pages 914-928, September.
  19. 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.
  20. Jessie J Hsu & Dianne M Finkelstein & David A Schoenfeld, 2015. "Outcome-Driven Cluster Analysis with Application to Microarray Data," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-15, November.
  21. Yip, Charles Chiu Hung & Ouyang, Xiangzi & Zhang, Xiao, 2025. "Measuring general cognitive ability in early elementary students: A shortened version of the Raven's Standard Progressive Matrices," Intelligence, Elsevier, vol. 112(C).
  22. Banerjee, Trambak & Mukherjee, Gourab & Radchenko, Peter, 2017. "Feature screening in large scale cluster analysis," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 191-212.
  23. 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.
  24. Philipp J. Kremer & Sangkyun Lee & Malgorzata Bogdan & Sandra Paterlini, 2017. "Sparse Portfolio Selection via the sorted $\ell_{1}$-Norm," Papers 1710.02435, arXiv.org.
  25. 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.
  26. Anubha Goel & Damir Filipovi'c & Puneet Pasricha, 2024. "Sparse Portfolio Selection via Topological Data Analysis based Clustering," Papers 2401.16920, arXiv.org, revised Dec 2024.
  27. Marion, Rebecca & Lederer, Johannes & Govaerts, Bernadette & von Sachs, Rainer, 2021. "VC-PCR: A Prediction Method based on Supervised Variable Selection and Clustering," LIDAM Discussion Papers ISBA 2021040, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  28. Zhang, Yingying & Wang, Huixia Judy & Zhu, Zhongyi, 2019. "Quantile-regression-based clustering for panel data," Journal of Econometrics, Elsevier, vol. 213(1), pages 54-67.
  29. 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.
  30. Ander Wilson & Brian J. Reich, 2014. "Confounder selection via penalized credible regions," Biometrics, The International Biometric Society, vol. 70(4), pages 852-861, December.
  31. Zhao, Shangwei & Ullah, Aman & Zhang, Xinyu, 2018. "A class of model averaging estimators," Economics Letters, Elsevier, vol. 162(C), pages 101-106.
  32. 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.
  33. 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).
  34. 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.
  35. Oikonomou, Ioannis & Platanakis, Emmanouil & Sutcliffe, Charles, 2018. "Socially responsible investment portfolios: Does the optimization process matter?," The British Accounting Review, Elsevier, vol. 50(4), pages 379-401.
  36. Philip Kostov & Thankom Arun & Samuel Annim, 2014. "Financial Services to the Unbanked: the case of the Mzansi intervention in South Africa," Contemporary Economics, Vizja University, vol. 8(2), June.
  37. 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.
  38. 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.
  39. 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.
  40. Jeon, Jong-June & Kwon, Sunghoon & Choi, Hosik, 2017. "Homogeneity detection for the high-dimensional generalized linear model," Computational Statistics & Data Analysis, Elsevier, vol. 114(C), pages 61-74.
  41. 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.
  42. Minami, Kentaro, 2020. "Degrees of freedom in submodular regularization: A computational perspective of Stein’s unbiased risk estimate," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
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