Estimation of variance components: what is missing in theEMalgorithm
- 1 July 1986
- journal article
- research article
- Published by Taylor & Francis in Journal of Statistical Computation and Simulation
- Vol. 24 (3-4) , 215-230
- https://doi.org/10.1080/00949658608810905
Abstract
The EM algorithm is a frequently advocated algorithm for the estimation of variance components. A faster converging algorithm is developed using alternative parameter-izations based on the analysis of variance. The procedure is exemplified using designs with two and three variance components and with multivariate designs using parameter values relevant to animal breeding data.Keywords
This publication has 11 references indexed in Scilit:
- A Mixed-Model Procedure for Analyzing Ordered Categorical DataPublished by JSTOR ,1984
- Statistical and Computational Aspects of Mixed Model AnalysisJournal of the Royal Statistical Society Series C: Applied Statistics, 1984
- Maximum Likelihood Procedures for Estimating Genetic Parameters for Later Lactations of Dairy CattleJournal of Dairy Science, 1983
- Computation of variance components using the em algorithmJournal of Statistical Computation and Simulation, 1982
- Sire EvaluationBiometrics, 1979
- Empirical Bayes methods for two-way contingency tablesBiometrika, 1978
- The Estimation of Heritability with Unbalanced Data: I. Observations Available on Parents and OffspringBiometrics, 1977
- Maximum Likelihood Approaches to Variance Component Estimation and to Related ProblemsJournal of the American Statistical Association, 1977
- Recovery of inter-block information when block sizes are unequalBiometrika, 1971
- The analysis of randomized experiments with orthogonal block structure. I. Block structure and the null analysis of varianceProceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 1965