Structural multivariate-univariate linear mixed model solver for multiple random effects allowing the specification of variance-covariance structures for random effects and allowing the fit of heterogeneous and special 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 relationship matrices or other covariance structures. Spatial models can be fitted using the two-dimensional spline functionality in sommer.
|Maintainer||Giovanny Covarrubias-Pazaran <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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