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：2004
卷号：66
期号：03
出版社：Indian Statistical Institute
摘要：In this paper, the asymptotic property and the performance of the repeated half sampling (RHS) criterion are investigated. In the context of variable selection under a linear regression model, we show that RHS is asymptotically equivalent to the multifold cross-validated (MCV) criterion. While in the case where the candidate family of models doesn't include the true model, we establish that RHS and also MCV are asymptotically equivalent to a criterion similar to Takeuchi information criterion (TIC). The performance of RHS criterion is compared with CV, Akaike, corrected Akaike and BIC criteria. The results of a simulation study show that RHS improve upon the performance of some criteria in two important areas of application: multiple linear regression and multivariate regression.
