Estimating Variance Components in a Class of Mixed Models by Restricted Maximum Likelihood

An efficient algorithm is described for computing restricted maximum likelihood estimates of variance components in a class of models. The class of models is characterized by effects to be absorbed, which are nested within herds, other fixed effects, random sire effects, one other group of random ef...

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Bibliographic Details
Published in:Journal of dairy science 1986-04, Vol.69 (4), p.1156-1165
Main Authors: Smith, S.P., Graser, H.-U.
Format: Article
Language:English
Subjects:
HATOS
HERDS
MATEMATICAS
MATHEMATICS
MATHEMATIQUE
MILK YIELD
MODELE
MODELOS
PADRES
PARENT
PARENTS
PATERNIDAD
PATERNITE
PATERNITY
RENDEMENT LAITIER
RENDIMIENTO LECHERO
TROUPEAU
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Summary:An efficient algorithm is described for computing restricted maximum likelihood estimates of variance components in a class of models. The class of models is characterized by effects to be absorbed, which are nested within herds, other fixed effects, random sire effects, one other group of random effects nested within herds, and a random residual. The model can be generalized to account for relationships among sires. Matrix inversion is not used. A realistic example is presented.
ISSN:0022-0302
1525-3198
DOI:10.3168/jds.s0022-0302(86)80516-1