R functions to estimate and perform goodness of fit test for several Markov regime switching and mixture bivariate copula models. The goodness of fit test is based on a Cramer von Mises statistic and uses the Rosenblatt transform and parametric bootstrap to estimate the p-value. The estimation of the copula parameters are based on the pseudo-maximum likelihood method using pseudo-observations defined as normalized ranks.
| Version: | 1.0.4 |
| Depends: | matrixcalc, mvtnorm, foreach, doParallel, copula |
| Imports: | stats |
| Published: | 2020-04-21 |
| Author: | Mamadou Yamar Thioub, Bouchra Nasri, Romanic Pieugueu, and Bruno Remillard |
| Maintainer: | Mamadou Yamar Thioub <mamadou-yamar.thioub at hec.ca> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | HMMcopula results |
| Reference manual: | HMMcopula.pdf |
| Package source: | HMMcopula_1.0.4.tar.gz |
| Windows binaries: | r-devel: HMMcopula_1.0.4.zip, r-release: HMMcopula_1.0.4.zip, r-oldrel: HMMcopula_1.0.4.zip |
| macOS binaries: | r-release: HMMcopula_1.0.4.tgz, r-oldrel: HMMcopula_1.0.4.tgz |
| Old sources: | HMMcopula archive |
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