sommer: Solving Mixed Model Equations in R

Multivariate linear mixed model solver for estimation of heterogeneous variances and specification of variance covariance structures. Maximum and Restricted Maximum Likelihood (ML/REML) estimates can be obtained using the Direct-Inversion Newton-Raphson (NR), Direct-Inversion Average Information (AI), MME-based Expectation-Maximization (EM), and 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 multivariate mixed model software. Multivariate models (multiple responses) can be fitted currently with NR, AI and EMMA algorithms.

Version: 2.8
Depends: R (≥ 2.10), Matrix (≥ 1.1.1), methods, stats, MASS, parallel
Suggests: knitr
Published: 2017-06-06
Author: Giovanny Covarrubias-Pazaran
Maintainer: Giovanny Covarrubias-Pazaran <cova_ruber at live.com.mx>
License: GPL-3
URL: http://www.wisc.edu
NeedsCompilation: no
Citation: sommer citation info
Materials: ChangeLog
CRAN checks: sommer results

Downloads:

Reference manual: sommer.pdf
Vignettes: Quantitative genetics using the sommer package
Package source: sommer_2.8.tar.gz
Windows binaries: r-devel: sommer_2.8.zip, r-release: sommer_2.8.zip, r-oldrel: sommer_2.8.zip
OS X El Capitan binaries: r-release: sommer_2.8.tgz
OS X Mavericks binaries: r-oldrel: sommer_2.8.tgz
Old sources: sommer archive

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