gaussian_example

Simulated data containing a Gaussian response variable <code>y</code> with two
covariates. The dataset was generated from a model with time-varying effects
of covariate <code>x</code> and the lagged value of the response variable, time-varying
intercept, and time-invariant effect of covariate <code>z</code>. The time-varying
coefficients vary according to a spline with 20 degrees of freedom.

datasets

Easy-to-use and efficient interface for
Bayesian inference of complex panel (time series) data using dynamic
multivariate panel models by Helske and Tikka (2024)
<doi:10.1016/j.alcr.2024.100617>. The package supports joint modeling of
multiple measurements per individual, time-varying and time-invariant
effects, and a wide range of discrete and continuous distributions.
Estimation of these dynamic multivariate panel models is carried out via
'Stan'. For an in-depth tutorial of the package, see
(Tikka and Helske, 2024) <doi:10.48550/arXiv.2302.01607>.

Santtu Tikka

dynamite

Bayesian Modeling and Causal Inference for Multivariate
Longitudinal Data

Jouni Helske

Nicholas Clark

Lucy D'Agostino McGowan

gaussian_example function

A data frame with 3000 rows and 5 variables:<dl>
<dt>y</dt>
<dd>The response variable.</dd><dt>x</dt>
<dd>A continuous covariate.</dd><dt>z</dt>
<dd>A binary covariate.</dd><dt>id</dt>
<dd>Variable defining individuals (1 to 50).</dd><dt>time</dt>
<dd>Variable defining the time point of the measurement (1 to 30).</dd>
</dl>

Format

Simulated Data of a Gaussian Response — gaussian_example

A data frame with 3000 rows and 5 variables:<dl>
<dt>y</dt>
<dd>The response variable.</dd>

<dt>x</dt>
<dd>A continuous covariate.</dd>

<dt>z</dt>
<dd>A binary covariate.</dd>

<dt>id</dt>
<dd>Variable defining individuals (1 to 50).</dd>

<dt>time</dt>
<dd>Variable defining the time point of the measurement (1 to 30).</dd>


</dl>

gaussian_example: Simulated Data of a Gaussian Response

Description

Usage

Arguments

Format

See Also