Subsampling based variable selection for generalized linear models

DOI10.1016/j.csda.2023.107740OpenAlexW4323925996MaRDI QIDQ6115531

Colin B. Begg, Marinela Capanu, Mihai C. Giurcanu, Mithat Gönen

Publication date: 13 July 2023

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2023.107740

zbMATH Keywords

variable selectionAICsubsamplingstability selectionscreening threshold

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08)

Cites Work

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• Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection
• Bagging predictors
• Nearly unbiased variable selection under minimax concave penalty
• The Adaptive Lasso and Its Oracle Properties
• Thresholding least-squares inference in high-dimensional regression models
• On bagging and nonlinear estimation
• Analyzing bagging
• Regularizing LASSO: A Consistent Variable Selection Method
• Asymptotic Statistics
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• A simulation based method for assessing the statistical significance of logistic regression models after common variable selection procedures
• Stability Selection
• Optimal Detection of Changepoints With a Linear Computational Cost
• Variable Selection with Error Control: Another Look at Stability Selection
• Regularization and Variable Selection Via the Elastic Net
• Model Selection and Estimation in Regression with Grouped Variables
• Regression modeling strategies. With applications to linear models, logistic regression and survival analysis

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