The impact of unsuspected serial correlations on model selection in linear regression

DOI10.1016/0167-7152(95)00052-6zbMath0855.62056OpenAlexW2017196626MaRDI QIDQ1916177

Clifford M. Hurvich, Chih-Ling Tsai

Publication date: 1 September 1996

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(95)00052-6

zbMATH Keywords

simulationAkaike information criterionstationary Gaussian processordinary least squarestrigonometric regressionSchwarz information criterion\(AIC\)\(BIC\)asymptotic probability of overfittingasymptotic probability of underfittingerror correlationsunsuspected serial correlations

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05)

Cites Work

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• Asymptotic properties of criteria for selection of variables in multiple regression
• Estimating the dimension of a model
• An optimal selection of regression variables

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