mkVarCorr

Make variance and correlation matrices from <code>theta</code>

Fit linear and generalized linear mixed-effects models.
The models and their components are represented using S4 classes and
methods.  The core computational algorithms are implemented using the
'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".

Ben Bolker

lme4

Linear Mixed-Effects Models using 'Eigen' and S4

Douglas Bates

Martin Maechler

Steven Walker

Rune Haubo Bojesen Christensen

Henrik Singmann

Bin Dai

Fabian Scheipl

Gabor Grothendieck

Peter Green

John Fox

Alexander Bauer

Pavel N. Krivitsky

Emi Tanaka

Mikael Jagan

mkVarCorr function

<dl> <dt>sc</dt>
<dd>scale factor (residual standard deviation).</dd> <dt>cnms</dt>
<dd>component names.</dd> <dt>nc</dt>
<dd>numeric vector: number of terms in each RE component.</dd> <dt>theta</dt>
<dd>theta vector (lower-triangle of Cholesky factors).</dd> <dt>nms</dt>
<dd>component names (FIXME: nms/cnms redundant:
 nms=names(cnms)?)</dd></dl>

Arguments

Make Variance and Correlation Matrices from theta — mkVarCorr

<dl>

 <dt>sc</dt>
<dd>scale factor (residual standard deviation).</dd>

 <dt>cnms</dt>
<dd>component names.</dd>

 <dt>nc</dt>
<dd>numeric vector: number of terms in each RE component.</dd>

 <dt>theta</dt>
<dd>theta vector (lower-triangle of Cholesky factors).</dd>

 <dt>nms</dt>
<dd>component names (FIXME: nms/cnms redundant:
 nms=names(cnms)?)</dd>

</dl>

Make Variance and Correlation Matrices from <code>theta</code>

mkVarCorr: Make Variance and Correlation Matrices from `theta`

Description

Usage

Value

Arguments

See Also