Structural multivariate-univariate linear mixed model solver for estimation of multiple random effects and unknown variance-covariance structures (i.e. heterogeneous and unstructured variance models) (Covarrubias-Pazaran, 2016 <doi:10.1371/journal.pone.0156744>; Maier et al., 2015 <doi:10.1016/j.ajhg.2014.12.006>). 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) and dense known covariance structures for levels of random effects. Spatial models can also be fitted using i.e. the two-dimensional spline functionality available in sommer.

Solving Mixed Model Equations in R

package-ubuntu-20.04-r-4.0.5#cran#sommer-4.1.3

<p>This function is extracts the random effects from a mixed model fitted by mmer.
</p>

<table summary="R argblock"><tr valign="top">
<td><code>object</code></td>
<td>
<p>an mmer object</p>
</td>
</tr></table>

<dl>
<dt>$randef</dt>
<dd>
<p> a list structure with the random effects or BLUPs.</p>
</dd>
</dl>

package-ubuntu-20.04-r-4.0.5#cran#sommer-4.1.3#docs#randef

randef

Description

Usage

Arguments

Value

Examples

sommer

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