sommer: Solving Mixed Model Equations in R

Structural multivariate-univariate linear mixed model solver for multiple random effects and estimation of unknown variance-covariance structures (i.e. heterogeneous and unstructured 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 Direct-Inversion Average Information 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 known relationship matrices and estimate complex unknown covariance structures. Spatial models can be fitted using the two-dimensional spline functionality in sommer.

Version: 3.9.3
Depends: R (≥ 2.10), Matrix (≥ 1.1.1), methods, stats, MASS, lattice, crayon
Imports: Rcpp (≥ 0.12.19)
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, plyr, parallel, orthopolynom
Published: 2019-04-03
Author: Giovanny Covarrubias-Pazaran
Maintainer: Giovanny Covarrubias-Pazaran <cova_ruber at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: sommer citation info
Materials: README ChangeLog
CRAN checks: sommer results


Reference manual: sommer.pdf
Vignettes: FAQ for the sommer package
Quantitative genetics using the sommer package
Moving to newer versions of sommer
Quick start for the sommer package
Package source: sommer_3.9.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: sommer_3.9.3.tgz, r-oldrel: sommer_3.8.tgz
Old sources: sommer archive

Reverse dependencies:

Reverse imports: pcgen
Reverse enhances: emmeans


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