Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/20619
Title: Technical note: A successive over-relaxation preconditioner to solve mixed model equations for genetic evaluation
Contributor(s): Meyer, Karin  (author)orcid 
Publication Date: 2016
DOI: 10.2527/jas.2016-0665
Handle Link: https://hdl.handle.net/1959.11/20619
Field of Research (FoR) 2008: 070201 Animal Breeding
Field of Research (FoR) 2020: 300305 Animal reproduction and breeding
Socio-Economic Objective (SEO) 2008: 830301 Beef Cattle
Socio-Economic Objective (SEO) 2020: 100401 Beef cattle
Abstract: A computationally efficient preconditioned conjugate gradient algorithm with a symmetric successive over-relaxation (SSOR) preconditioner for the iterative solution of set mixed model equations is described. The potential computational savings of this approach are examined for an example of single-step genomic evaluation of Australian sheep. Results show that the SSOR preconditioner can substantially reduce the number of iterates required for solutions to converge compared with simpler preconditioners with marked reductions in overall computing time.
Publication Type: Journal Article
Source of Publication: Journal of Animal Science, 94(11), p. 4530-4535
Publisher: American Society of Animal Science
Place of Publication: United States of America
ISSN: 0021-8812
1525-3163
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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Appears in Collections:Animal Genetics and Breeding Unit (AGBU)
Journal Article

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