Akaike Information Criterion for Selecting Variables in the Nested Error Regression Model

DOI10.1080/03610926.2011.555043zbMath1271.62159OpenAlexW2073416268MaRDI QIDQ2920064

Tatsuya Kubokawa, Muni S. Srivastava

Publication date: 23 October 2012

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2011.555043

zbMATH Keywords

random effectsanalysis of variancesmall area estimationlinear mixed modelnested error regression modelselection of variables

Mathematics Subject Classification ID

Point estimation (62F10) Parametric inference (62F99) Analysis of variance and covariance (ANOVA) (62J10)

Cites Work

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• Estimation of the mean of a multivariate normal distribution
• Further analysis of the data by Akaike's information criterion and the finite corrections
• Conditional Akaike information for mixed-effects models
• The Estimation of the Mean Squared Error of Small-Area Estimators
• On Information and Sufficiency
• A new look at the statistical model identification

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