Consistency of high-dimensional AIC-type andCp-type criteria in multivariate linear regression
نویسندگان
چکیده
منابع مشابه
High-Dimensional AIC and Consistency Properties of Several Criteria in Multivariate Linear Regression
The AIC and Cp and their modifications have been proposed for multivariate linear regression models under a large-sample framework when the sample size n is large, but the dimension p is fixed. In this paper, first we propose a high-dimensional AIC (denoted by HAIC) which is approximately unbiased estimator of the risk under a highdimensional framework such that p/n → c ∈ (0, 1). It is noted th...
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It is common knowledge that the Akaike’s information criterion (AIC) is not a consistent model selection criterion. This inconsistency property has been confirmed from an asymptotic selection probability evaluated from a large-sample asymptotic framework. However, when a high-dimensional asymptotic framework, such that the dimension of the response variables and the sample size are approaching ...
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The model selection criteria AIC, BIC and Cp have been proposed for estimation of the rank of coefficient matrix in multivariate linear model. In general, it is known that under a large-sample asymptotic framework AIC and Cp is not consistent, but BIC is consistent. However, we note that these criteria have consistency when the number p of the response variables and the sample size n are large ...
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ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 2014
ISSN: 0047-259X
DOI: 10.1016/j.jmva.2013.09.006