plot.mvgam_fevd

This function takes an <code>mvgam_fevd</code> object and produces
a plot of the posterior median contributions to forecast variance for each series
in the fitted Vector Autoregression

Fit Bayesian Dynamic Generalized Additive Models to multivariate observations. Users can build nonlinear State-Space models that can incorporate semiparametric effects in observation and process components, using a wide range of observation families. Estimation is performed using Markov Chain Monte Carlo with Hamiltonian Monte Carlo in the software 'Stan'. References: Clark & Wells (2022) <doi:10.1111/2041-210X.13974>.

Nicholas J Clark

mvgam

Multivariate (Dynamic) Generalized Additive Models

Sarah Heaps

Scott Pease

Matthijs Hollanders

plot.mvgam_fevd function

<dl><dt>x</dt>
<dd><code>list</code> object of class <code>mvgam_fevd</code>. See <code>fevd()</code></dd>
<dt>...</dt>
<dd>ignored</dd></dl>

Arguments

Author

Plot forecast error variance decompositions from an mvgam_fevd object — plot.mvgam_fevd

<dl>

<dt>x</dt>
<dd><code>list</code> object of class <code>mvgam_fevd</code>. See <code>fevd()</code></dd>


<dt>...</dt>
<dd>ignored</dd>

</dl>

plot.mvgam_fevd: Plot forecast error variance decompositions from an `mvgam_fevd` object

Description

Usage

Value

Arguments

Author