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Variable selection with error control: another look at stability selection

Citations

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Cited by:

  1. Khurram Nadeem & Mehdi-Abderrahman Jabri, 2023. "Stable variable ranking and selection in regularized logistic regression for severely imbalanced big binary data," PLOS ONE, Public Library of Science, vol. 18(1), pages 1-26, January.
  2. Max Grazier G'Sell & Stefan Wager & Alexandra Chouldechova & Robert Tibshirani, 2016. "Sequential selection procedures and false discovery rate control," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 423-444, March.
  3. Solari, Aldo & Djordjilović, Vera, 2022. "Multi split conformal prediction," Statistics & Probability Letters, Elsevier, vol. 184(C).
  4. Chung Shing Rex Ha & Martina Müller-Nurasyid & Agnese Petrera & Stefanie M Hauck & Federico Marini & Detlef K Bartsch & Emily P Slater & Konstantin Strauch, 2023. "Proteomics biomarker discovery for individualized prevention of familial pancreatic cancer using statistical learning," PLOS ONE, Public Library of Science, vol. 18(1), pages 1-21, January.
  5. Huang, Shih-Ting & Xie, Fang & Lederer, Johannes, 2021. "Tuning-free ridge estimators for high-dimensional generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).
  6. Panxu Yuan & Yinfei Kong & Gaorong Li, 2024. "FDR control and power analysis for high-dimensional logistic regression via StabKoff," Statistical Papers, Springer, vol. 65(5), pages 2719-2749, July.
  7. Sohrabi, Narges & Movaghari, Hadi, 2020. "Reliable factors of Capital structure: Stability selection approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 296-310.
  8. Michael Balzer & Elisabeth Bergherr & Swen Hutter & Tobias Hepp, 2026. "Gradient boosting for Dirichlet regression models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 110(1), pages 149-189, March.
  9. Jana Janková & Rajen D. Shah & Peter Bühlmann & Richard J. Samworth, 2020. "Goodness‐of‐fit testing in high dimensional generalized linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 773-795, July.
  10. Marzia Freo & Alessandra Luati, 2024. "Lasso-based variable selection methods in text regression: the case of short texts," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(1), pages 69-99, March.
  11. Claude Renaux & Laura Buzdugan & Markus Kalisch & Peter Bühlmann, 2020. "Hierarchical inference for genome-wide association studies: a view on methodology with software," Computational Statistics, Springer, vol. 35(1), pages 1-40, March.
  12. Weikang Zhang & Alison Watts, 2025. "HODL Strategy or Fantasy? 480 Million Crypto Market Simulations and the Macro-Sentiment Effect," Papers 2512.02029, arXiv.org.
  13. Jacob Bien & Irina Gaynanova & Johannes Lederer & Christian L. Müller, 2019. "Prediction error bounds for linear regression with the TREX," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 451-474, June.
  14. 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).
  15. Tino Werner, 2025. "Loss-guided stability selection," 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. 19(1), pages 5-30, March.
  16. Timothy I. Cannings & Richard J. Samworth, 2017. "Random-projection ensemble classification," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(4), pages 959-1035, September.
  17. Guo, Peiyang & Lam, Jacqueline C.K. & Li, Victor O.K., 2019. "Drivers of domestic electricity users’ price responsiveness: A novel machine learning approach," Applied Energy, Elsevier, vol. 235(C), pages 900-913.
  18. 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.
  19. Ruben Dezeure & Peter Bühlmann & Cun-Hui Zhang, 2017. "High-dimensional simultaneous inference with the bootstrap," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(4), pages 685-719, December.
  20. Loann David Denis Desboulets, 2018. "A Review on Variable Selection in Regression Analysis," Econometrics, MDPI, vol. 6(4), pages 1-27, November.
  21. 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.
  22. Aurélien Sallin & Simone Balestra, 2022. "The Earth is Not Flat: A New World of High-Dimensional Peer Effects," Economics of Education Working Paper Series 0189, University of Zurich, Department of Business Administration (IBW).
  23. Claude Renaux & Laura Buzdugan & Markus Kalisch & Peter Bühlmann, 2020. "Rejoinder on: Hierarchical inference for genome-wide association studies: a view on methodology with software," Computational Statistics, Springer, vol. 35(1), pages 59-67, March.
  24. Armeen Taeb & Parikshit Shah & Venkat Chandrasekaran, 2020. "False discovery and its control in low rank estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(4), pages 997-1027, September.
  25. Emma Schwager & Himel Mallick & Steffen Ventz & Curtis Huttenhower, 2017. "A Bayesian method for detecting pairwise associations in compositional data," PLOS Computational Biology, Public Library of Science, vol. 13(11), pages 1-21, November.
  26. Michael Balzer & Adhen Benlahlou, 2025. "Mitigating consequences of prestige in citations of publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(11), pages 6035-6062, November.
  27. Juan Torres Munguía, 2024. "Identifying Gender-Specific Risk Factors for Income Poverty across Poverty Levels in Urban Mexico: A Model-Based Boosting Approach," Social Sciences, MDPI, vol. 13(3), pages 1-21, March.
  28. Juan Armando Torres Munguía, 2024. "A model-based boosting approach to risk factors for physical intimate partner violence against women and girls in Mexico," Journal of Computational Social Science, Springer, vol. 7(2), pages 1937-1963, October.
  29. Sonja Greven & Fabian Scheipl, 2020. "Comments on: Inference and computation with Generalized Additive Models and their extensions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(2), pages 343-350, June.
  30. Chun-Xia Zhang & Jiang-She Zhang & Sang-Woon Kim, 2016. "PBoostGA: pseudo-boosting genetic algorithm for variable ranking and selection," Computational Statistics, Springer, vol. 31(4), pages 1237-1262, December.
  31. D García Rasines & G A Young, 2023. "Splitting strategies for post-selection inference," Biometrika, Biometrika Trust, vol. 110(3), pages 597-614.
  32. Lu Lin & Feng Li, 2023. "Global debiased DC estimations for biased estimators via pro forma regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(2), pages 726-758, June.
  33. Gillard, Jonathan & Zhigljavsky, Anatoly, 2018. "Optimal estimation of direction in regression models with large number of parameters," Applied Mathematics and Computation, Elsevier, vol. 318(C), pages 281-289.
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