sommer: Solving Mixed Model Equations in R

Multivariate mixed model solver for multiple random effects allowing the specification of variance covariance structures. ML/REML estimates are obtained using the Average Information (AI), Expectation-Maximization (EM), Newton-Raphson (NR), or Efficient Mixed Model Association (EMMA) algorithms. Designed for genomic prediction and genome wide association studies (GWAS) to include additive, dominance and epistatic relationship structures or other covariance structures in R, but also functional as a regular mixed model program. Multivariate models (multiple responses) can be fitted currently with NR, AI and EMMA algorithms allowing multiple random effects as well. Covariance structures for the residual component is currently supported only for balanced univariate Newton Raphson models.

Version: 2.5
Depends: R (≥ 2.10), Matrix (≥ 1.1.1), methods, stats, MASS, parallel
Suggests: knitr
Published: 2017-01-03
Author: Giovanny Covarrubias-Pazaran
Maintainer: Giovanny Covarrubias-Pazaran <cova_ruber at>
License: GPL-3
NeedsCompilation: no
Citation: sommer citation info
Materials: ChangeLog
CRAN checks: sommer results


Reference manual: sommer.pdf
Vignettes: Genetic analysis using the sommer package
Package source: sommer_2.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: sommer_2.5.tgz, r-oldrel: sommer_2.5.tgz
Old sources: sommer archive


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