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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install.packages("sommer")

4.0.8 by Giovanny Covarrubias-Pazaran, 3 months 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, statgenGWAS.

Enhanced by emmeans.


See at CRAN