MANOVA type tests under a convex discrepancy function for the standard multivariate linear model

DOI10.1016/0378-3758(93)90103-DzbMath0772.62030WikidataQ127830743 ScholiaQ127830743MaRDI QIDQ2368342

C. Radhakrishna Rao, Zhi-Dong Bai, Lin Cheng Zhao

Publication date: 24 August 1993

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

zbMATH Keywords

convex function\(M\)-estimationMANOVAtesting linear hypothesesleast squares techniquesconsistent estimates of nuisance parametersRao's score type statisticroots of determinantal equationsstandard multivariate linear modelWald type statistic

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Asymptotic distribution theory in statistics (62E20) Hypothesis testing in multivariate analysis (62H15)

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Cites Work

• Asymptotic normality of minimum \(L_ 1\)-norm estimates in linear models
• M-methods in multivariate linear models
• Asymptotic relations between the likelihood estimating function and the maximum likelihood estimator
• Asymptotic theory of least distances estimate in multivariate linear models
• Asymptotic normality ofr-estimates in the linear model
• Robust analysis of variance based upon a likelihood ratio criterion
• TESTS OF SIGNIFICANCE IN MULTIVARIATE ANALYSIS
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