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

<code>coef</code> method for class <code>"mmer"</code>.

## S3 method for class 'mmer'
coef(object, ...)

<table summary="R argblock">
<tr valign="top">
<td><code>object</code></td>
<td>
an object of class <code>"mmer"</code>
</td>
</tr>
<tr valign="top">
<td><code>...</code></td>
<td>
Further arguments to be passed
</td>
</tr>
</table>

Giovanny Covarrubias <a href="mailto:covarrubiasp@wisc.edu">covarrubiasp@wisc.edu</a>

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

`object`	an object of class `"mmer"`
`...`	Further arguments to be passed

coef

Description

Usage

Arguments

Value

Author(s)

See Also

sommer

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