Equivalence testing of mean vector and covariance matrix for multi-populations under a two-step monotone incomplete sample
This paper investigates the hypothesis testing of a mean vector and covariance matrix for multi-populations in the context of two-step monotone incomplete data drawn from Np+q(μ,Σ), a multivariate normal population with mean μ and covariance matrix Σ. Three null hypotheses are considered, and the likelihood ratio criterion and Wald-type criterion are derived. On the basis of numerical simulations, the test that employs the Wald-type criterion is recommended.
Year of publication: |
2014
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Authors: | Tsukada, Shin-ichi |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 132.2014, C, p. 183-196
|
Publisher: |
Elsevier |
Subject: | Mean vector | Covariance matrix | Likelihood ratio criterion | Wald-type criterion | Monotone incomplete data |
Saved in:
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