Prediction error criterion for selecting variables in a linear regression model

DOI10.1007/S10463-009-0233-5zbMath1432.62207OpenAlexW2010369110MaRDI QIDQ907107

N. E. Zubov

Publication date: 1 February 2016

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10463-009-0233-5

zbMATH Keywords

risk functionlinear regression modelsselection criteriaselection of variablesprediction error criterion

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Statistical ranking and selection procedures (62F07)

Related Items (3)

Variable selection in multivariate linear regression with random predictors ⋮ Consistent variable selection criteria in multivariate linear regression even when dimension exceeds sample size ⋮ High-dimensional consistencies of KOO methods in multivariate regression model and discriminant analysis

Cites Work

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• More Comments on C P
• Further analysis of the data by Akaike's information criterion and the finite corrections
• Modified AIC and Cp in multivariate linear regression
• The Relationship between Variable Selection and Data Agumentation and a Method for Prediction
• Model Selection for Multivariate Regression in Small Samples
• Mean Square Error of Prediction as a Criterion for Selecting Variables
• Some Comments on C P

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