Testing a covariance matrix: exact null distribution of its likelihood criterion

DOI10.1080/00949650802294237zbMath1178.62062OpenAlexW2019837664MaRDI QIDQ3653253

Thu Pham Gia, Noyan Turkkan

Publication date: 22 December 2009

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949650802294237

zbMATH Keywords

simulationlikelihood ratiocovariancemultivariate distributionLambert functionMeijer functionnull distribution

Mathematics Subject Classification ID

Related Items (2)

Simultaneous testing of mean vector and covariance matrix for high-dimensional data ⋮ Testing the equality of several covariance matrices

Cites Work

• Exact distribution of the generalized Wilks's statistic and applications
• On the Lambert \(w\) function
• On some tests of the covariance matrix under general conditions
• Distributions of Characteristic Roots in Multivariate Analysis Part I. Null Distributions
• Distributions of characteristic roots in multivariate analysis Part II. Non-Null Distribution
• Statistical Discrimination Analysis Using the Maximum Function
• On the distribution of a statistic used for testing a covariance matrix
• Percentile approximations for a class of likelihood ratio criteria
• Distribution of the likelihood ratio criterion for testing a hypothesis specifying a covariance matrix
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