Asreml-r users variance-covariance matrix

Asreml r users variance covariance matrix full#
Asreml r users variance covariance matrix code#

A good converter from letter code to numeric format is implemented in the function atcg1234, which supports higher ploidy levels than diploid. In addition the pin function can be used to estimate standard errors for linear combinations of variance components (i.e.

Asreml r users variance covariance matrix full#

The package provides flexibility to fit other genetic models such as full and half diallel models as well. The package provides kernels to estimate additive ( A.mat), dominance ( D.mat), and epistatic ( E.mat) relationship matrices for diploid and polyploid organisms. This package returns variance-covariance components, BLUPs, BLUEs, residuals, fitted values, variances-covariances for fixed and random effects, etc. The core of the package are the mmer2 (formula-based) and mmer (matrix-based) functions that fit the multivariate linear mixed models.We highly recommend the use of the formula-based mmer2 function since it offers the same flexibility but makes easier the tedious work of building the matrices.

The sommer package has been developed to provide R users with open-source code to understand how most popular likelihood algorithms in mixed model analysis work, but at the same time allowing to perform their real analysis in diploid and polyploid organisms with small and medium-size data sets ( n problem and dense covariance structures when the direct-inversion algorithm become faster than MME-based 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. ML/REML estimates can be obtained using the Direct-Inversion Newton-Raphson and Efficient Mixed Model Association algorithms. Sommer is a structural multivariate-univariate linear mixed model solver for multiple random effects allowing the specification of variance covariance structures. Sommer-package: Solving Mixed Model Equations in R

Asreml-r users variance-covariance matrix