Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.laa.2006.02.013
Title: Two step-down tests for equality of covariance matrices
Authors: Chaudhuri, S. 
Perlman, M.D.
Keywords: Bartlett's test
Likelihood ratio test
Multivariate normal distributions
Precision matrices
Simultaneous confidence regions
Step-down tests
Testing equality of covariance matrices
Unbiased tests
Issue Date: 1-Aug-2006
Citation: Chaudhuri, S., Perlman, M.D. (2006-08-01). Two step-down tests for equality of covariance matrices. Linear Algebra and Its Applications 417 (1 SPEC. ISS.) : 42-63. ScholarBank@NUS Repository. https://doi.org/10.1016/j.laa.2006.02.013
Abstract: The classical problem of testing the equality of the covariance matrices from k ≥ 2 p-dimensional normal populations is reexamined. The likelihood ratio (LR) statistic, also called Bartlett's statistic, can be decomposed in two ways, corresponding to two distinct component-wise decompositions of the null hypothesis in terms of the covariance matrices or precision matrices, respectively. The factors of the LR statistic that appear in these two decompositions can be interpreted as conditional and unconditional LR statistics for the component-wise null hypotheses, and their mutual independence under the null hypothesis allows the determination of the overall significance level. © 2006 Elsevier Inc. All rights reserved.
Source Title: Linear Algebra and Its Applications
URI: http://scholarbank.nus.edu.sg/handle/10635/105446
ISSN: 00243795
DOI: 10.1016/j.laa.2006.02.013
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