A new REML (parameter expanded) EM algorithm for linear mixed models
Author:
Affiliation:
1. Centre for Bioinformatics and Biometrics; University of Wollongong; Wollongong NSW 2522 Australia
2. Mathematical Sciences Institute; Australian National University; Canberra ACT 0200 Australia
Funder
Grains Research Development Corporation
NSW Department of Primary Industries
Publisher
Wiley
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Link
http://onlinelibrary.wiley.com/wol1/doi/10.1111/anzs.12208/fullpdf
Reference22 articles.
1. Butler , D. 2009 asreml: asreml() fits the linear mixed model www.vsni.co.uk
2. Some new algorithms for computing restricted maximum likelihood estimates of variance components;Callanan;Journal of Statistical Computation and Simulation,1991
3. PERSPECTIVES OF ANOVA, REML AND A GENERAL LINEAR MIXED MODEL
4. Maximum likelihood from incomplete data via the EM algorithm;Dempster;Journal of the Royal Statistical Society, Series B,1977
5. EM-REML estimation of covariance parameters in Gaussian mixed models for longitudinal data analysis;Foulley;Genetics Selection Evolution,2000
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