Solving Mixed Model Equations in R

Structural multivariate-univariate linear mixed model solver for estimation of multiple random effects and unknown variance-covariance structures (i.e. heterogeneous and unstructured variance models) (Covarrubias-Pazaran, 2016 ; Maier et al., 2015 ). 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) and dense known covariance structures for levels of random effects. Spatial models can also be fitted using i.e. the two-dimensional spline functionality available in sommer.


To install this source on your computer type in the R terminal

library(devtools)

install_github('covaruber/sommer')

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Reference manual

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install.packages("sommer")

4.0.1 by Giovanny Covarrubias-Pazaran, 17 days ago


Browse source code at https://github.com/cran/sommer


Authors: Giovanny Covarrubias-Pazaran


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp

Depends on Matrix, methods, stats, MASS, lattice, crayon

Suggests knitr, plyr, parallel, orthopolynom

Linking to Rcpp, RcppArmadillo


Imported by mlmm.gwas, pcgen.

Enhanced by emmeans.


See at CRAN