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|Title:||Technical note: A successive over-relaxation preconditioner to solve mixed model equations for genetic evaluation||Contributor(s):||Meyer, Karin (author)||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
|Peer Reviewed:||Yes||HERDC Category Description:||C1 Refereed Article in a Scholarly Journal||Statistics to Oct 2018:||Visitors: 11|
|Appears in Collections:||Animal Genetics and Breeding Unit (AGBU)|
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