Robust VIF regression with application to variable selection in large data sets

DOI10.1214/12-AOAS584zbMath1454.62214arXiv1304.5349MaRDI QIDQ1951534

Debbie J. Dupuis, Maria-Pia Victoria-Feser

Publication date: 6 June 2013

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1304.5349

zbMATH Keywords

\(M\)-estimatorlinear regressionvariable selectionmulticollinearitycollege data

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (5)

A robust sparse linear approach for contaminated data ⋮ A novel group VIF regression for group variable selection with application to multiple change-point detection ⋮ Variable selection by searching for good subsets ⋮ Regular, median and Huber cross‐validation: A computational comparison ⋮ Discussion of: ``The power of monitoring: how to make the most of a contaminated multivariate sample

Uses Software

• UCI-ml
• glmnet
• foba

Cites Work

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