demoLGCM

Simulated Data From a Latent Growth Curve Model.

datasets

Provides an implementation of Gaussian process panel modeling (GPPM).
GPPM is described in Karch, Brandmaier & Voelkle (2020; <DOI:10.3389/fpsyg.2020.00351>) and Karch (2016; <DOI:10.18452/17641>).
Essentially, GPPM is Gaussian process based modeling of longitudinal panel data.
'gppm' also supports regular Gaussian process regression (with a focus on flexible model specification), and multi-task learning.

Julian Karch

gppm

Gaussian Process Panel Modeling

demoLGCM function

A data frame with 1998 rows and 3 variables:<dl>
<dt>ID</dt>
<dd>Subject ID</dd><dt>t</dt>
<dd>Time index</dd><dt>y</dt>
<dd>Generic measurement</dd>
</dl>

Format

Simulated Data From a Latent Growth Curve Model. — demoLGCM

A data frame with 1998 rows and 3 variables:<dl>
<dt>ID</dt>
<dd>Subject ID</dd>

<dt>t</dt>
<dd>Time index</dd>

<dt>y</dt>
<dd>Generic measurement</dd>


</dl>

demoLGCM: Simulated Data From a Latent Growth Curve Model.

Description

Usage

Arguments

Format