Some new algorithms for computing restricted maximum likelihood estimates of variance components

1991 ◽  
Vol 38 (1-4) ◽  
pp. 239-259 ◽  
Author(s):  
Terrance P. Callanan ◽  
David A. Harville
1979 ◽  
Vol 28 (1-4) ◽  
pp. 125-142 ◽  
Author(s):  
Kalyan Das

In this paper we study the asymptotic optimality of the restricted maximum likelihood estimates of variance components in the mixed model of analysis of variance. Using conceptual design sequences of Miller (1977), under slightly stronger conditions, we show that the restricted maximum likelihood estimates are not only asymptotically normal, but also asymptotically equivalent to the maximum likelihood estimates in a reasonable sense.


1998 ◽  
Vol 49 (4) ◽  
pp. 607 ◽  
Author(s):  
S. J. Schoeman ◽  
G. G. Jordaan

Postweaning liveweight gain records of 1610 young bulls obtained both in feedlot and under pasture were used to estimate (co)variance components using a multivariate restricted maximum likelihood analysis. The pedigree file included 3477 animals. Heritability estimates for liveweights and gain in both environments correspond to most previously reported estimates. The genetic correlation of gain between the 2 environments was -0·12, suggesting a large genotype testing environment interaction and re-ranking of animal breeding values across environments. Results of this analysis suggest the need for environment-specific breeding values for postweaning gain.


1990 ◽  
Vol 66 (2) ◽  
pp. 379-386 ◽  
Author(s):  
George A. Marcoulides

This study compares, using simulated data, two methods for estimating variance components in generalizability (G) studies. Traditionally variance components are estimated from an analysis of variance of sample data. The alternative method for estimating variance components is restricted maximum likelihood (REML). The results indicate that REML provides estimates for the components in the various designs that are closer to the true parameters than the estimates from analysis of variance.


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