plot.mvgam_irf

This function takes an <code>mvgam_irf</code> object and produces plots of Impulse Response Functions

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_irf function

<dl><dt>x</dt>
<dd><code>list</code> object of class <code>mvgam_irf</code>. See <code>irf()</code></dd>
<dt>series</dt>
<dd><code>integer</code> specifying which process series should be given the shock</dd>
<dt>...</dt>
<dd>ignored</dd></dl>

Arguments

Author

Plot impulse responses from an mvgam_irf object — plot.mvgam_irf

<dl>

<dt>x</dt>
<dd><code>list</code> object of class <code>mvgam_irf</code>. See <code>irf()</code></dd>


<dt>series</dt>
<dd><code>integer</code> specifying which process series should be given the shock</dd>


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

</dl>

plot.mvgam_irf: Plot impulse responses from an `mvgam_irf` object

Description

Usage

Value

Arguments

Author