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 variance models. ML/REML estimates can be obtained using the Direct-Inversion Newton-Raphson, and Efficient Mixed Model Association algorithms. Designed for genomic prediction and genome wide association studies (GWAS) to include additive, dominance and epistatic relationship structures or other covariance structures, but also functional as a regular mixed model program.
|Date of publication||2017-08-24 08:25:49 UTC|
|Maintainer||Giovanny Covarrubias-Pazaran <[email protected]>|
|Package repository||View on CRAN|
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