Implements parameter estimation using a Bayesian approach for Multivariate Threshold Autoregressive (MTAR) models with missing data using Markov Chain Monte Carlo methods. Performs the simulation of MTAR processes (mtarsim()), estimation of matrix parameters and the threshold values (mtarns()),  identification of the autoregressive orders using Bayesian variable selection (mtarstr()), identification of the number of regimes using Metropolised Carlin and Chib (mtarnumreg()) and estimate missing data, coefficients and covariance matrices conditional on the autoregressive orders, the threshold values and the number of regimes (mtarmissing()). Calderon and Nieto (2017) <doi:10.1080/03610926.2014.990758>.

Bayesian Approach for MTAR Models with Missing Data

package-ubuntu-20.04-r-4.0.5#cran#BMTAR-0.1.1

<p>Auxiliary function of some functions in the MTAR package
</p>

<table summary="R argblock">
<tr valign="top">
<td><code>M</code></td>
<td>
<p>matrix type object</p>
</td>
</tr>
<tr valign="top">
<td><code>r</code></td>
<td>
<p>integer indicating the length of the list</p>
</td>
</tr>
</table>

package-ubuntu-20.04-r-4.0.5#cran#BMTAR-0.1.1#docs#repM

repM

Description

Usage

Arguments

Value

BMTAR

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`M`	matrix type object
`r`	integer indicating the length of the list