文章基本信息

标题：CONSISTENT PROCEDURES FOR MIXED LINEAR MODEL SELECTION
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作者：JIMING JIANG University of California, Davis, USA ; J. SUNIL RAO Case Western Reserve University, Cleveland, USA
期刊名称：Sankhya. Series A, mathematical statistics and probability
印刷版ISSN：0976-836X
电子版ISSN：0976-8378
出版年度：2003
卷号：65
期号：01
页码：23--42
出版社：Indian Statistical Institute
摘要：We consider the problem of selecting the fixed and random effects in a mixed linear model. Two kinds of selection problems are considered. The first is to select the fixed covariates from a set of candidate predictors when the random effects are not subject to selection; the second is to select both the fixed covariates and the random effect factors. Our selection criteria are similar to the generalized information criterion (GIC), but we show that a naive GIC does not work for the second kind of selection problem. Asymptotic theory is developed in which we give sufficient conditions for consistency of the selection criteria proposed. Finite sample performance of the selection procedures are investigated by simulation studies.
关键词：Consistency, mixed effects models, model selection.