An accurate test for the equality of covariance matrices from decomposable graphical Gaussian models

DOI10.1002/cjs.11201zbMath1349.62230OpenAlexW1514665307MaRDI QIDQ5413639

Hélène Massam, Yan Yan Wu, Augustine C. M. Wong

Publication date: 30 April 2014

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/cjs.11201

zbMATH Keywords

decomposable graphical modelscumulant generating functionequality of covariance matricesLugannani and Rice formulaadjusted likelihood ratio test statisticBartlett-Box M-statistic

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Hypothesis testing in multivariate analysis (62H15) Graphical methods in statistics (62A09)

Cites Work

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• Flexible covariance estimation in graphical Gaussian models
• Unbiasedness of the likelihood ratio tests for equality of several covariance matrices and equality of several multivariate normal populations
• Hyper Markov laws in the statistical analysis of decomposable graphical models
• Regularized estimation of large covariance matrices
• Wishart distributions for decomposable graphs
• Saddlepoint Approximations with Applications
• Saddlepoint expansions for conditional distributions
• Saddle point approximation for the distribution of the sum of independent random variables
• Saddlepoint approximations for P-values of some tests of covariance matrices
• Covariance matrix selection and estimation via penalised normal likelihood
• Properties of Power Functions of Some Tests Concerning Dispersion Matrices of Multivariate Normal Distributions
• Essentials of Statistical Inference
• Properties of sufficiency and statistical tests

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