Equivalence testing of mean vector and covariance matrix for multi-populations under a two-step monotone incomplete sample

DOI10.1016/j.jmva.2014.08.005zbMath1360.62291OpenAlexW2048803912MaRDI QIDQ458650

Shin-ichi Tsukada

Publication date: 8 October 2014

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2014.08.005

zbMATH Keywords

covariance matrixmean vectorlikelihood ratio criterionmonotone incomplete dataWald-type criterion

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20) Hypothesis testing in multivariate analysis (62H15)

Related Items

Bartlett correction to the likelihood ratio test for MCAR with two‐step monotone sample ⋮ Asymptotic properties of a correlation matrix under a two-step monotone incomplete sample ⋮ Unbiased estimator for a covariance matrix in a three-step monotone incomplete sample ⋮ Multivariate normality test based on kurtosis with two-step monotone missing data ⋮ On the likelihood ratio test for the equality of multivariate normal populations with two-step monotone missing data

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