Journal ArticleDOI
A Derivative-Free Approach for Estimating Variance Components in Animal Models by Restricted Maximum Likelihood
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This article is published in Journal of Animal Science.The article was published on 1987-05-01. It has received 347 citations till now. The article focuses on the topics: Restricted maximum likelihood & Likelihood function.read more
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Journal ArticleDOI
Efficient Control of Population Structure in Model Organism Association Mapping
Hyun Min Kang,Noah Zaitlen,Claire M. Wade,Claire M. Wade,Andrew Kirby,Andrew Kirby,David Heckerman,Mark J. Daly,Mark J. Daly,Eleazar Eskin +9 more
TL;DR: A new method, efficient mixed-model association (EMMA), which corrects for population structure and genetic relatedness in model organism association mapping and takes advantage of the specific nature of the optimization problem in applying mixed models for association mapping, which allows for substantially increase the computational speed and reliability of the results.
Book ChapterDOI
Estimating and Interpreting Heritability for Plant Breeding: An Update
Journal ArticleDOI
Average information REML: An efficient algorithm for variance parameter estimation in linear mixed models
TL;DR: In this article, a strategy of using an average information matrix is shown to be computationally convenient and efficient for estimating variance components by restricted maximum likelihood (REML) in the mixed linear model.
Journal ArticleDOI
Variance components due to direct and maternal effects for growth traits of Australian beef cattle
TL;DR: Variance components for birth, weaning, yearling and final weight in Australian Hereford, Angus and Zebu Cross cattle were estimated by Restricted Maximum Likelihood and there were marked differences between breeds in the relative magnitude ofh2 and the maternal heritability, and the direct-maternal genetic correlation.
Journal ArticleDOI
Restricted maximum likelihood to estimate variance components for animal models with several random effects using a derivative-free algorithm
TL;DR: Estimates are obtained by evaluating the likelihood explicitly and using standard, derivative-free optimization procedures to locate its maximum by the so-called Animal Model, which includes the additive genetic merit of animals as a random effect, and incorporates all information on relationships between animals.