create_plot_df

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

create_plot_df function

<dl><dt>object</dt>
<dd>model or fit</dd>
<dt>x</dt>
<dd>x-axis variable name</dd>
<dt>group_by</dt>
<dd>grouping variable name (use <code>NULL</code> for no grouping)</dd></dl>

Arguments

Helper function for plots — create_plot_df

<dl>

<dt>object</dt>
<dd>model or fit</dd>


<dt>x</dt>
<dd>x-axis variable name</dd>


<dt>group_by</dt>
<dd>grouping variable name (use <code>NULL</code> for no grouping)</dd>

</dl>

create_plot_df: Helper function for plots

Description

Usage

Value

Arguments