SimHMMCop

Simulaion of values from a bivariate Markov regime switching copula model

Estimation procedures and goodness-of-fit test for several Markov regime switching models and mixtures of bivariate copula models. The goodness-of-fit test is based on a Cramer-von Mises statistic and uses Rosenblatt's transform and parametric bootstrap to estimate the p-value. The proposed methodologies are described in Nasri, Remillard and Thioub (2020) <doi:10.1002/cjs.11534>.

Bruno Remillard

HMMcopula

Markov Regime Switching Copula Models Estimation and
Goodness-of-Fit

Romanic Pieugueu

SimHMMCop function

<dl><dt>Q</dt>
<dd>Transition probality matrix (d x d);</dd>
<dt>family</dt>
<dd>'gaussian' , 't' , 'clayton' , 'frank' , 'gumbel'</dd>
<dt>KendallTau</dt>
<dd>Kendall's rank correlation</dd>
<dt>n</dt>
<dd>number of simulated vectors</dd>
<dt>DoF</dt>
<dd>degree of freedom only for the Student copula</dd></dl>

Arguments

Simulation of bivariate Markov regime switching copula model — SimHMMCop

<dl>

<dt>Q</dt>
<dd>Transition probality matrix (d x d);</dd>


<dt>family</dt>
<dd>'gaussian' , 't' , 'clayton' , 'frank' , 'gumbel'</dd>


<dt>KendallTau</dt>
<dd>Kendall's rank correlation</dd>


<dt>n</dt>
<dd>number of simulated vectors</dd>


<dt>DoF</dt>
<dd>degree of freedom only for the Student copula</dd>

</dl>

SimHMMCop: Simulation of bivariate Markov regime switching copula model

Description

Usage

Value

Arguments

Examples