Asymptotic power of likelihood ratio tests for high dimensional data
Statistics Theory
2013-02-15 v1 Statistics Theory
Abstract
This paper considers the asymptotic power of likelihood ratio test (LRT) for the identity test when the dimension p is large compared to the sample size n. The asymptotic distribution of LRT under alternatives is given and an explicit expression of the power is derived. A simulation study is carried out to compare LRT with other tests. All these studies show that LRT is a powerful test to detect eigenvalues around zero. Key words and phrases: Covariance matrix, High dimensional data, Identity test, Likelihood ratio test, Power
Keywords
Cite
@article{arxiv.1302.3302,
title = {Asymptotic power of likelihood ratio tests for high dimensional data},
author = {Cheng Wang and Longbing Cao and Baiqi Miao},
journal= {arXiv preprint arXiv:1302.3302},
year = {2013}
}
Comments
10 pages, 2 figures