simuVAR

This function simulates a vector autoregresive process.

Implementation of hypothesis testing procedures described in Hansen (1992) <doi:10.1002/jae.3950070506>, Carrasco, Hu, & Ploberger (2014) <doi:10.3982/ECTA8609>, Dufour & Luger (2017) <doi:10.1080/07474938.2017.1307548>, and Rodriguez Rondon & Dufour (2024) <https://grodriguezrondon.com/files/RodriguezRondon_Dufour_2024_MonteCarlo_LikelihoodRatioTest_MarkovSwitchingModels_20241015.pdf> that can be used to identify the number of regimes in Markov switching models.

Gabriel Rodriguez Rondon

MSTest

Hypothesis Testing for Markov Switching Models

Jean-Marie Dufour

simuVAR function

<dl><dt>mdl_h0</dt>
<dd>List containing the following DGP parameters<ul>
<li>n: Length of series.</li>
<li>mu: A (<code>q x 1</code>) vector of means.</li>
<li>sigma: A (<code>q x q</code>) covariance matrix.</li>
<li>phi: A (<code>q x qp</code>) matrix of autoregressive coefficients.</li>
<li>p: Number of autoregressive lags.</li>
<li>q: Number of series.</li>
<li>eps: An optional (<code>T+burnin x q</code>) matrix with standard normal errors to be used. Errors will be generated if not provided.</li>
</ul></dd>
<dt>burnin</dt>
<dd>Number of simulated observations to remove from beginning. Default is <code>100</code>.</dd></dl>

Arguments

Simulate VAR process — simuVAR

<dl>

<dt>mdl_h0</dt>
<dd>List containing the following DGP parameters<ul>
<li>n: Length of series.</li>
<li>mu: A (<code>q x 1</code>) vector of means.</li>
<li>sigma: A (<code>q x q</code>) covariance matrix.</li>
<li>phi: A (<code>q x qp</code>) matrix of autoregressive coefficients.</li>
<li>p: Number of autoregressive lags.</li>
<li>q: Number of series.</li>
<li>eps: An optional (<code>T+burnin x q</code>) matrix with standard normal errors to be used. Errors will be generated if not provided.</li>
</ul></dd>


<dt>burnin</dt>
<dd>Number of simulated observations to remove from beginning. Default is <code>100</code>.</dd>

</dl>

simuVAR: Simulate VAR process

Description

Usage

Value

Arguments