simage

models

Fit relationship-based and customized mixed-effects models with complex variance-covariance structures using the 'lme4' machinery. The core computational algorithms are implemented using the
'Eigen' 'C++' library for numerical linear algebra and 'RcppEigen' 'glue'.

Giovanny Covarrubias-Pazaran

lme4breeding

Relationship-Based Mixed-Effects Models

simage function

<dl> <dt>data</dt>
<dd>model data of class <code>"data.frame"</code></dd> <dt>Var1</dt>
<dd>variable to set in the x axis</dd> <dt>Var2</dt>
<dd>variable to set in the y axis</dd> <dt>...</dt>
<dd>Further arguments to be passed to the image function.</dd></dl>

Arguments

Author

Image of sparsity between two variables — simage

<dl>

 <dt>data</dt>
<dd>model data of class <code>"data.frame"</code></dd>

 <dt>Var1</dt>
<dd>variable to set in the x axis</dd>

 <dt>Var2</dt>
<dd>variable to set in the y axis</dd>

 <dt>...</dt>
<dd>Further arguments to be passed to the image function.</dd>

</dl>

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simage: Image of sparsity between two variables

Description

Usage

Value

Arguments

Author

See Also