The Annals of Statistics

Asymptotic Expansions of the Non-Null Distributions of Likelihood Ratio Criteria for Covariance Matrices

C. G. Khatri and M. S. Srivastava

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Abstract

In this paper, asymptotic expansions of the non-null distributions of the likelihood ratio criteria are obtained for testing the hypotheses: (a) $H_1: \Sigma = \sigma^2I, \sigma^2 > 0$, (b) $H_2: \Sigma_1 = \Sigma_2$, against alternatives which are close to the hypothesis. These expansions are of chi-square type. The first problem has been considered by Sugiura (1969) but because of the singularity at the hypothesis, his expansion will not be good for alternatives close to the hypothesis. The second problem has been considered by de Waal (1970) but the expansion given by him is invalid.

Article information

Source
Ann. Statist., Volume 2, Number 1 (1974), 109-117.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176342617

Digital Object Identifier
doi:10.1214/aos/1176342617

Mathematical Reviews number (MathSciNet)
MR345317

Zentralblatt MATH identifier
0296.62037

JSTOR
links.jstor.org

Subjects
Primary: 62H10: Distribution of statistics
Secondary: 62E20: Asymptotic distribution theory 62H15: Hypothesis testing

Keywords
Asymptotic non-null distributions likelihood ratio tests sphericity equality of covariances chi-square distribution

Citation

Khatri, C. G.; Srivastava, M. S. Asymptotic Expansions of the Non-Null Distributions of Likelihood Ratio Criteria for Covariance Matrices. Ann. Statist. 2 (1974), no. 1, 109--117. doi:10.1214/aos/1176342617. https://projecteuclid.org/euclid.aos/1176342617


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