Information criteria for variable selection under sparsity

DOI10.1093/biomet/ast055zbMath1400.62042OpenAlexW2048390594MaRDI QIDQ5410310

Maarten Jansen

Publication date: 16 April 2014

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://dipot.ulb.ac.be/dspace/bitstream/2013/133291/1/jansen13ICsparsityreprint.pdf

zbMATH Keywords

high-dimensional datavariable selectioninformation criterionsparsitylassoMallows' \(C_p\)

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Statistical ranking and selection procedures (62F07)

Related Items (4)

Discussion on: “A Scale-Free Approach for False Discovery Rate Control in Generalized Linear Models” by Dai, Lin, Zing, Liu ⋮ Bias-corrected Kullback-Leibler distance criterion based model selection with covariables missing at random ⋮ Information criteria bias correction for group selection ⋮ Generalized cross validation in variable selection with and without shrinkage

Uses Software

• ThreshLab

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