MSVARmdl_em

Estimate Markov-switching vector autoregressive model by EM algorithm. This function is used by <code>MSVARmdl</code> which organizes the output and takes raw data as input.

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_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

MSVARmdl_em function

<dl><dt>theta_0</dt>
<dd>vector with initial values for parameters.</dd>
<dt>mdl</dt>
<dd>List with model attributes.</dd>
<dt>k</dt>
<dd>Integer determining the number of regimes.</dd>
<dt>optim_options</dt>
<dd>List with optimization options.</dd></dl>

Arguments

Estimation of Markov-switching vector autoregressive model by EM Algorithm — MSVARmdl_em

<dl>

<dt>theta_0</dt>
<dd>vector with initial values for parameters.</dd>


<dt>mdl</dt>
<dd>List with model attributes.</dd>


<dt>k</dt>
<dd>Integer determining the number of regimes.</dd>


<dt>optim_options</dt>
<dd>List with optimization options.</dd>

</dl>

MSVARmdl_em: Estimation of Markov-switching vector autoregressive model by EM Algorithm

Description

Usage

Value

Arguments

References