Computation of variance components using the em algorithm

DOI10.1080/00949658208810550zbMath0478.65084OpenAlexW1976032076MaRDI QIDQ3936151

Nan M. Laird

Publication date: 1982

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949658208810550

zbMATH Keywords

maximum likelihoodanalysis of varianceestimators of variance components

Mathematics Subject Classification ID

Numerical solutions to equations with linear operators (65J10) Probabilistic methods, stochastic differential equations (65C99)

Related Items (10)

Efficient estimation of variance components in nonparametric mixed-effects models with large samples ⋮ Making REML computationally feasible for large data sets: use of the Gibbs sampler ⋮ An algorithm for searching optimal variance component estimators in linear mixed models ⋮ Ml estimation in the bivariate poisson distribution in the presence of missing values via the em algorithm ⋮ On a matrix identity associated with generalized least squares ⋮ A fast Monte Carlo expectation–maximization algorithm for estimation in latent class model analysis with an application to assess diagnostic accuracy for cervical neoplasia in women with atypical glandular cells ⋮ On elliptical multilevel models ⋮ Estimation in mixed models via layer triangular transformation ⋮ ML estimation for the multivariate normal distribution with general linear model mea1 and linear-structure covariance matrix; one-population, complete-data case ⋮ Some new algorithms for computing restricted maximum likelihood estimates of variance components

Cites Work

• Extension of the Gauss-Markov theorem to include the estimation of random effects
• Bayesian inference for variance components using only error contrasts
• Maximum-likelihood estimation for the mixed analysis of variance model

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