HMmdl_mle

This function computes estimate a Hidden Markov model using MLE.

internal

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_2025_MonteCarlo_LikelihoodRatioTest_MarkovSwitchingModels_20251014.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

HMmdl_mle function

<dl><dt>theta_0</dt>
<dd>vector containing initial values to use in optimization</dd>
<dt>mdl_in</dt>
<dd>List with model properties (can be obtained from estimating linear model i.e., using <code>ARmdl</code>)</dd>
<dt>k</dt>
<dd>integer determining the number of regimes</dd>
<dt>optim_options</dt>
<dd>List containing<ul>
<li>maxit: maximum number of iterations.</li>
<li>thtol: convergence criterion.</li>
</ul></dd></dl>

Arguments

Hidden Markov model maximum likelihood estimation — HMmdl_mle

<dl>

<dt>theta_0</dt>
<dd>vector containing initial values to use in optimization</dd>


<dt>mdl_in</dt>
<dd>List with model properties (can be obtained from estimating linear model i.e., using <code>ARmdl</code>)</dd>


<dt>k</dt>
<dd>integer determining the number of regimes</dd>


<dt>optim_options</dt>
<dd>List containing<ul>
<li>maxit: maximum number of iterations.</li>
<li>thtol: convergence criterion.</li>
</ul></dd>

</dl>

HMmdl_mle: Hidden Markov model maximum likelihood estimation

Description

Usage

Value

Arguments