Bootstrapping function needed for parallel computing
bootstrapfun(Q, family, tau, n, df, max_iter, eps, HMM)Estimated copula parameters
Estimated transition matrix
Estimated probabilites for regimes
Estimated Kendall's tau
Estimated degrees of freedom for the Student copula
Estimated pseudo-observations
Estimated Cramer-von Mises statistic
Weights vector (1 x reg or component);
'gaussian' , 't' , 'clayton' , 'frank' , 'gumbel'
Kendall's rank correlation
number of simulated vectors
vector of degree of freedom (d x 1), only for the Student copula.
maximum number of iterations for estimation
precision (e.g 0.00001);
1 (if HMM) , 0 (if mixture);
Mamadou Yamar Thioub and Bruno Remillard, April 12, 2018