A variable selection proposal for multiple linear regression analysis

DOI10.1080/00949655.2010.518569zbMath1431.62290OpenAlexW2095611227MaRDI QIDQ5300735

S. J. Steel, D. W. Uys

Publication date: 28 June 2013

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2010.518569

zbMATH Keywords

LassoLarsunbiased risk estimationlimited translationpre-test selection

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Cites Work

• Parametric robustness: Small biases can be worthwhile
• ``Preconditioning for feature selection and regression in high-dimensional problems
• Least angle and \(\ell _{1}\) penalized regression: a review
• Estimation of the mean of a multivariate normal distribution
• Least angle regression. (With discussion)
• Model Selection and Model Averaging
• Simultaneous selection and estimation for the some zeros family of normal models
• Limiting the Risk of Bayes and Empirical Bayes Estimators--Part I: The Bayes Case
• Some Comments on C P

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