Likelihood ratio test for one-sided hypothesis of covariance matrices of two normal populations

DOI10.1080/03610928708829564zbMath0631.62065OpenAlexW2084060060MaRDI QIDQ3768196

Toshio Sakata

Publication date: 1987

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610928708829564

zbMATH Keywords

Monte Carlolikelihood ratio testmultivariate normal populationslimiting distributioncovariance matricestwo sample problemscomparisons of powerone- sided hypothesis

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Hypothesis testing in multivariate analysis (62H15)

Related Items (1)

One-sided test of a covariance matrix with a known null value

Cites Work

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• Asymptotic expansions for the joint and marginal distributions of the latent roots of \(S_1S^{-1}_2\)
• Power comparisons of two-sided tests of equality of two covariance matrices based on six criteria
• On tests for detecting change in mean
• Asymptotic expansions of the distributions of the latent roots and the latent vector of the Wishart and multivariate F matrices
• A Note on the Generation of Random Normal Deviates
• A test of a multivariate normal mean with composite hypotheses determined by linear inequalities
• A multivariate correction for attenuation
• Power Comparisons of Tests of Equality of Two Covariance Matrices Based on Individual Characteristic Roots
• A multivariate analogue of the one-sided test
• Properties of sufficiency and statistical tests

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