Variable Selection Methods in High-dimensional Regression—A Simulation Study

DOI10.1080/03610918.2013.833231zbMath1474.62270OpenAlexW2030453926WikidataQ60487793 ScholiaQ60487793MaRDI QIDQ5860257

Susana Faria, Shirin Shahriari, A. Manuela Gonçalves

Publication date: 19 November 2021

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2013.833231

zbMATH Keywords

bootstraphigh-dimensional datavariable selectionpartial least-squares regressionprinciple component regression

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Linear regression; mixed models (62J05)

Related Items

Variable selection in double/debiased machine learning for causal inference: an outcome-adaptive approach

Uses Software

• R
• pls
• elasticnet
• spls
• ElemStatLearn

Cites Work

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