lgpscaling-class

lgpscaling

An S4 class to represent variable scaling

Interpretable nonparametric modeling of longitudinal data
using additive Gaussian process regression. Contains functionality
for inferring covariate effects and assessing covariate relevances.
Models are specified using a convenient formula syntax, and can include
shared, group-specific, non-stationary, heterogeneous and temporally
uncertain effects. Bayesian inference for model parameters is performed
using 'Stan'. The modeling approach and methods are described in detail in
Timonen et al. (2021) <doi:10.1093/bioinformatics/btab021>.

Juho Timonen

lgpr

Longitudinal Gaussian Process Regression

Andrew Johnson

lgpscaling-class function

<dl>
<dt><code>loc</code></dt>
<dd>original location (mean)</dd></dl>
<dt><code>scale</code></dt>
<dd>original scale (standard deviation)</dd>
<dt><code>var_name</code></dt>
<dd>variable name</dd>

Slots

An S4 class to represent variable scaling — lgpscaling-class

<dl>
<dt><code>loc</code></dt>
<dd>original location (mean)</dd>


<dt><code>scale</code></dt>
<dd>original scale (standard deviation)</dd>


<dt><code>var_name</code></dt>
<dd>variable name</dd>


</dl>

lgpscaling-class: An S4 class to represent variable scaling

Description

Arguments

Slots