Asymptotic power of likelihood ratio tests for high dimensional data

Cheng Wang

Statistics & Probability Letters, 2014, vol. 88, issue C, 184-189

Abstract: 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.

Keywords: Covariance matrix; High dimensional data; Identity test; Likelihood ratio test; Power; Stein’s loss (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.spl.2014.02.010

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