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 ; 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) 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.


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")

3.9.3 by Giovanny Covarrubias-Pazaran, 2 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 pcgen.

Enhanced by emmeans.


See at CRAN