Goodness-of-fit test of a Markov regime switching bivariate copula model
GofHMMCop(R, reg, family, max_iter, eps, n_sample, n_cores)pvalue (significant when the result is greater than 5)
(1 x reg) estimated parameter of the copula according to CRAN copula package (except for Frank copula, where theta = log(theta_R_Package)) for each regime (except for degrees of freedom)
estimated degree of freedom, only for the Student copula
(reg x reg) estimated transition matrix
(n x reg) conditional probabilities of being in regime k at time t given observations up to time t
estimated Kendall tau for each regime
(n x 2) matrix of Rosenblatt transforms
Cramer-von-Mises statistic for goodness-of-fit
regime probabilities for the conditional distribution given the past Kendall's tau
(n x 2) data matrix that will be transformed to pseudo-observations
number of regimes
'gaussian' , 't' , 'clayton' , 'frank' , 'gumbel'
maxmimum number of iterations of the EM algorithm
precision (stopping criteria); suggestion 0.0001
number of bootstrap; suggestion 1000
number of cores to use in the parallel computing
<doi::10.1002/cjs.11534>