The advantage of decomposing elaborate hypotheses on covariance matrices into conditionally independent hypotheses in building near-exact distributions for the test statistics

DOI10.1016/j.laa.2008.07.003zbMath1160.62055OpenAlexW2019304333WikidataQ125157158 ScholiaQ125157158MaRDI QIDQ1017618

Filipe J. Marques, Carlos A. Coelho

Publication date: 12 May 2009

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.laa.2008.07.003

zbMATH Keywords

mixturesgeneralized near-integer gamma distributionlikelihood ratio test statisticsconditionally independent hypothesesgeneralized sphericity testsnear-exact distributions

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Hypothesis testing in multivariate analysis (62H15) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (12)

The block sphericity test-exact and near-exact distributions for the likelihood ratio statistic ⋮ Testing the equality of several linear regression models ⋮ Likelihood ratio tests for elaborate covariance structures and for MANOVA models with elaborate covariance structures -- a review ⋮ The Block-Matrix Sphericity Test: Exact and Near-Exact Distributions for the Test Statistic ⋮ The Multi-Sample Block-Scalar Sphericity Test: Exact and Near-Exact Distributions for Its Likelihood Ratio Test Statistic ⋮ Near-exact distributions for the likelihood ratio test statistic of the multi-sample block-matrix sphericity test ⋮ Near-exact distributions for the likelihood ratio test statistic for testing multisample independence -- the real and complex cases ⋮ The simultaneous test of equality and circularity of several covariance matrices ⋮ Near-exact distributions for certain likelihood ratio test statistics ⋮ Testing simultaneously different covariance block diagonal structures – the multi-sample case ⋮ The exact and near-exact distributions of the main likelihood ratio test statistics used in the complex multivariate normal setting ⋮ A general near-exact distribution theory for the most common likelihood ratio test statistics used in multivariate analysis

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