[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5351/KJAS.2009.22.1.197

On Information Criteria in Linear Regression Model

Park, Man-Sik (Dept. of Biostatistics, Korea University)

Publication Information

The Korean Journal of Applied Statistics / v.22, no.1, 2009 , pp. 197-204 More about this Journal

Abstract

In the model selection problem, the main objective is to choose the true model from a manageable set of candidate models. An information criterion gauges the validity of a statistical model and judges the balance between goodness-of-fit and parsimony; "how well observed values ran approximate to the true values" and "how much information can be explained by the lower dimensional model" In this study, we introduce some information criteria modified from the Akaike Information Criterion (AIC) and the Bayesian Information Criterion(BIC). The information criteria considered in this study are compared via simulation studies and real application.

Keywords

Linear regression; information criterion; model selection;

Citations & Related Records

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