Asymptotic power of likelihood ratio tests for high dimensional data

This paper studies the asymptotic power of the likelihood ratio test (LRT) for the identity test when the dimension p is large compared to the sample size n. The asymptotic distribution under local alternatives is derived and a simulation study is carried out to compare LRT with other tests. All these studies show that LRT is a powerful test to detect small eigenvalues.

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Year of publication:	2014
Authors:	Wang, Cheng
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 88.2014, C, p. 184-189
Publisher:	Elsevier
Subject:	Covariance matrix \| High dimensional data \| Identity test \| Likelihood ratio test \| Power \| Stein’s loss

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010752974