sommer (3.9.1)

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.

Maintainer: Giovanny Covarrubias-Pazaran
Author(s): Giovanny Covarrubias-Pazaran

License: GPL (>= 2)

Uses: crayon, lattice, MASS, Matrix, Rcpp, orthopolynom, plyr, knitr
Reverse enhances: emmeans

Released 5 months ago.