Explicit maximum likelihood estimates from balanced data in the mixed model of the analysis of variance

DOI10.1214/aos/1176345073zbMath0465.62069OpenAlexW2068113462MaRDI QIDQ1154764

John J. Miller, Ted H. Szatrowski

Publication date: 1980

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1176345073

zbMATH Keywords

mixed modelvariance component estimationbalanced dataexplicit maximum likelihood estimates

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Point estimation (62F10) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (14)

Maximum likelihood estimation in mixed normal models with two variance Components ⋮ The spectral decomposition of covariance matrices for the variance components models ⋮ MANOVA in the multivariate components of variance model ⋮ REML estimation: Asymptotic behavior and related topics ⋮ Generalized dispersion matrices for covariance structural analysis ⋮ Experimental designs for mean and variance estimation in variance components models ⋮ A matrix inequality and its statistical application ⋮ ML estimation for the multivariate normal distribution with general linear model mea1 and linear-structure covariance matrix; one-population, complete-data case ⋮ Estimability of variance components when all model matrices commute ⋮ Bayesian multi-way balanced nested MANOVA models with random effects and a large number of the main factor levels ⋮ On the maximum likelihood estimation for certain MANOVA models ⋮ Likelihood ratio tests for covariance hypotheses generating commutative quadratic subspaces ⋮ The growth curve model: a review ⋮ Existence of maximum likelihood estimates in normal variance-components models

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