Bias-corrected AIC for selecting variables in multinomial logistic regression models

DOI10.1016/J.LAA.2012.01.018zbMath1238.62082OpenAlexW2024196575WikidataQ112882189 ScholiaQ112882189MaRDI QIDQ414719

Kenichi Satoh, Shinpei Imori, Hirokazu Yanagihara, Ken-ichi Kamo

Publication date: 11 May 2012

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.laa.2012.01.018

zbMATH Keywords

MLEvariable selectionpartial differential operator

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Generalized linear models (logistic models) (62J12)

Related Items (3)

An \(\ell_{2,0}\)-norm constrained matrix optimization via extended discrete first-order algorithms ⋮ Simple Formula for Calculating Bias‐corrected AIC in Generalized Linear Models ⋮ Jackknife bias correction of the AIC for selecting variables in canonical correlation analysis under model misspecification

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Cites Work

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• Bias correction of AIC in logistic regression models
• Invariants and likelihood ratio statistics
• Information criteria and statistical modeling.
• Bias-Corrected AIC for Selecting Variables in Poisson Regression Models
• Model Selection and Multimodel Inference
• On Information and Sufficiency
• The bootstrap and Edgeworth expansion
• A new look at the statistical model identification

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