autoplot.summary.normaliw

This function draws density plot for coefficient matrices of Minnesota prior VAR model.

Tools to model and forecast multivariate time series
including Bayesian Vector heterogeneous autoregressive (VHAR) model
by Kim & Baek (2023) (<doi:10.1080/00949655.2023.2281644>).
'bvhar' can model Vector Autoregressive (VAR), VHAR, Bayesian VAR (BVAR), and Bayesian VHAR (BVHAR) models.

Young Geun Kim

bvhar

Bayesian Vector Heterogeneous Autoregressive Modeling

Changryong Baek

autoplot.summary.normaliw function

<dl><dt>object</dt>
<dd>A <code>summary.normaliw</code> object</dd>
<dt>type</dt>
<dd>The type of the plot. Trace plot (<code>trace</code>), kernel density plot (<code>dens</code>), and interval estimates plot (<code>area</code>).</dd>
<dt>pars</dt>
<dd>Parameter names to draw.</dd>
<dt>regex_pars</dt>
<dd>Regular expression parameter names to draw.</dd>
<dt>...</dt>
<dd>Other options for each <code>bayesplot::mcmc_trace()</code>, <code>bayesplot::mcmc_dens()</code>, and <code>bayesplot::mcmc_areas()</code>.</dd></dl>

Arguments

Density Plot for Minnesota Prior VAR Model — autoplot.summary.normaliw

<dl>

<dt>object</dt>
<dd>A <code>summary.normaliw</code> object</dd>


<dt>type</dt>
<dd>The type of the plot. Trace plot (<code>trace</code>), kernel density plot (<code>dens</code>), and interval estimates plot (<code>area</code>).</dd>


<dt>pars</dt>
<dd>Parameter names to draw.</dd>


<dt>regex_pars</dt>
<dd>Regular expression parameter names to draw.</dd>


<dt>...</dt>
<dd>Other options for each <code>bayesplot::mcmc_trace()</code>, <code>bayesplot::mcmc_dens()</code>, and <code>bayesplot::mcmc_areas()</code>.</dd>

</dl>

autoplot.summary.normaliw: Density Plot for Minnesota Prior VAR Model

Description

Usage

Value

Arguments