sigma.LmME

Extract the SD of the error term of an LmME model.

Likelihood-based estimation of mixed-effects transformation models
using the Template Model Builder ('TMB', Kristensen et al., 2016)
<doi:10.18637/jss.v070.i05>. The technical details of transformation models
are given in Hothorn et al. (2018) <doi:10.1111/sjos.12291>. Likelihood
contributions of exact, randomly censored (left, right, interval) and
truncated observations are supported. The random effects are assumed to be
normally distributed on the scale of the transformation function, the
marginal likelihood is evaluated using the Laplace approximation, and the
gradients are calculated with automatic differentiation (Tamasi & Hothorn,
2021) <doi:10.32614/RJ-2021-075>. Penalized smooth shift terms can be
defined using 'mgcv'.

Balint Tamasi

tramME

Transformation Models with Mixed Effects

Torsten Hothorn

sigma.LmME function

<dl><dt>object</dt>
<dd>An <code>LmME</code> object.</dd>
<dt>...</dt>
<dd>Optional argument (for consistency with generic).</dd></dl>

Arguments

Extract the SD of the error term of an LmME model. — sigma.LmME

<dl>

<dt>object</dt>
<dd>An <code>LmME</code> object.</dd>


<dt>...</dt>
<dd>Optional argument (for consistency with generic).</dd>

</dl>

sigma.LmME: Extract the SD of the error term of an LmME model.

Description

Usage

Value

Arguments

Examples