plot_coefs

Plots sample quantiles from posterior predictive sample.
See <code>bayesplot::ppc_ribbon()</code> for details.

Efficient Bayesian generalized linear models with time-varying coefficients
as in Helske (2022, <doi:10.1016/j.softx.2022.101016>). Gaussian, Poisson, and binomial
observations are supported. The Markov chain Monte Carlo (MCMC) computations are done using
Hamiltonian Monte Carlo provided by Stan, using a state space representation
of the model in order to marginalise over the coefficients for efficient sampling.
For non-Gaussian models, the package uses the importance sampling type estimators based on
approximate marginal MCMC as in Vihola, Helske, Franks (2020, <doi:10.1111/sjos.12492>).

Jouni Helske

walker

Bayesian Generalized Linear Models with Time-Varying
Coefficients

plot_coefs function

<dl><dt>object</dt>
<dd>An output from <code>walker()</code>.</dd>
<dt>level</dt>
<dd>Level for intervals. Default is 0.05, leading to 90% intervals.</dd>
<dt>alpha</dt>
<dd>Transparency level for <code><a href="https://ggplot2.tidyverse.org/reference/geom_ribbon.html">ggplot2::geom_ribbon()</a></code>.</dd>
<dt>transform</dt>
<dd>Optional vectorized function for transforming the coefficients (for example <code>exp</code>).</dd>
<dt>scales</dt>
<dd>Should y-axis of the panels be <code>"fixed"</code> (default) or <code>"free"</code>?</dd>
<dt>add_zero</dt>
<dd>Logical, should a dashed line indicating a zero be included?</dd></dl>

Arguments

Posterior predictive check for walker object — plot_coefs

<dl>

<dt>object</dt>
<dd>An output from <code>walker()</code>.</dd>


<dt>level</dt>
<dd>Level for intervals. Default is 0.05, leading to 90% intervals.</dd>


<dt>alpha</dt>
<dd>Transparency level for <code><a href='https://ggplot2.tidyverse.org/reference/geom_ribbon.html'>ggplot2::geom_ribbon()</a></code>.</dd>


<dt>transform</dt>
<dd>Optional vectorized function for transforming the coefficients (for example <code>exp</code>).</dd>


<dt>scales</dt>
<dd>Should y-axis of the panels be <code>"fixed"</code> (default) or <code>"free"</code>?</dd>


<dt>add_zero</dt>
<dd>Logical, should a dashed line indicating a zero be included?</dd>

</dl>

plot_coefs: Posterior predictive check for walker object

Description

Usage

Arguments