Literature DB >> 27898940

Technical note: A successive over-relaxation preconditioner to solve mixed model equations for genetic evaluation.

K Meyer.   

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.

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Year:  2016        PMID: 27898940     DOI: 10.2527/jas.2016-0665

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  1 in total

1.  Convergence behavior of single-step GBLUP and SNPBLUP for different termination criteria.

Authors:  Jeremie Vandenplas; Mario P L Calus; Herwin Eding; Mathijs van Pelt; Rob Bergsma; Cornelis Vuik
Journal:  Genet Sel Evol       Date:  2021-04-09       Impact factor: 4.297

  1 in total

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