sommer: Solving Mixed Model Equations in R

Structural multivariate-univariate linear mixed model solver for multiple random effects allowing the specification of variance-covariance structures for random effects and allowing the fit of heterogeneous variance models (Covarrubias-Pazaran, 2016 <doi:10.1371/journal.pone.0156744>; Maier et al., 2015 <doi:10.1016/j.ajhg.2014.12.006>). ML/REML estimates can be obtained using the Direct-Inversion Newton-Raphson, and Efficient Mixed Model Association algorithms. Designed for genomic prediction and genome wide association studies (GWAS), particularly focused in the p > n problem (more coefficients than observations) to include multiple relationship matrices or other covariance structures. Spatial models can be fitted using the two-dimensional spline functionality in sommer.

Version: 3.5
Depends: R (≥ 2.10), Matrix (≥ 1.1.1), methods, stats, MASS, lattice
Imports: data.table
Suggests: knitr, plyr
Published: 2018-07-02
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
Quick start for the sommer package
Package source: sommer_3.5.tar.gz
Windows binaries: r-devel: sommer_3.5.zip, r-release: sommer_3.5.zip, r-oldrel: sommer_3.5.zip
OS X binaries: r-release: sommer_3.5.tgz, r-oldrel: sommer_3.5.tgz
Old sources: sommer archive

Reverse dependencies:

Reverse imports: mlmm.gwas

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