vcov.mtar

Computes estimates of the variance–covariance matrices for the scale
parameters of a fitted multivariate TAR model.

Estimation, inference and forecasting using the Bayesian approach for multivariate threshold autoregressive (TAR) models in which the distribution used to describe the noise process belongs to the class of Gaussian variance mixtures.

Luis Hernando Vanegas

mtarm

Bayesian Estimation of Multivariate Threshold Autoregressive
Models

Sergio Alejandro Calderón

Luz Marina Rondón

vcov.mtar function

<dl><dt>object</dt>
<dd>an object of class <code>mtar</code>, typically obtained from a call to
<code>mtar()</code>.</dd>
<dt>...</dt>
<dd>additional arguments passed to <code>FUN</code>.</dd>
<dt>FUN</dt>
<dd>a function to be applied to the MCMC chains of the scale parameters in order
to obtain point estimates. By default, <code>FUN</code> is set to <code><a href="/link/mean()?package=mtarm&version=0.1.8" data-mini-rdoc="mtarm::mean()">mean()</a></code>.</dd></dl>

Arguments

vcov method for objects of class mtar — vcov.mtar

<dl>

<dt>object</dt>
<dd>an object of class <code>mtar</code>, typically obtained from a call to
<code>mtar()</code>.</dd>


<dt>...</dt>
<dd>additional arguments passed to <code>FUN</code>.</dd>


<dt>FUN</dt>
<dd>a function to be applied to the MCMC chains of the scale parameters in order
to obtain point estimates. By default, <code>FUN</code> is set to <code><a href='https://rdrr.io/r/base/mean.html'>mean()</a></code>.</dd>

</dl>

vcov.mtar: vcov method for objects of class `mtar`

Description

Usage

Value

Arguments