R (>= 1.9.0), copula, foreach, parallel, doParallel
SparseGrid, numDeriv, VineCopula, methods, stats, MASS, utils

R (>= 1.9.0), copula (>= 0.999-15), foreach, parallel,
doParallel, R.utils
SparseGrid, numDeriv, VineCopula (>= 2.0.4), methods, stats,
MASS, utils
Several GoF tests for Copulae are provided. A new hybrid test is implemented which supports all of the individual tests. Estimation methods for the margins are provided. All the tests support parameter estimation and predefined values. The parameters are estimated by pseudo maximum likelihood but if it fails the estimation switches automatically to inversion of Kendall's tau. All the tests support automatized parallelization of the bootstrapping tasks.

SparseGrid, numDeriv, VineCopula (>= 2.0.5), methods, stats,
MASS, utils

Ostap Okhrin <ostap.okhrin@tu-dresden.de>,
Simon Trimborn <simon.trimborn@nus.edu.sg>,
Shulin Zhang <slzhang@swufe.edu.cn>,
Qian M. Zhou <qmzhou@sfu.ca>

Ostap Okhrin <ostap.okhrin@tu-dresden.de>,
Simon Trimborn <simon.trimborn@nus.edu.sg>,
Martin Waltz <martin.waltz@tu-dresden.de>
R (>= 1.9.0), copula (>= 0.999-15), foreach, parallel, doSNOW,
R.utils
SparseGrid, numDeriv, VineCopula (>= 2.0.5), methods, stats,
MASS, utils, yarrr, progress
Several Goodness-of-Fit (GoF) tests for Copulae are provided. A new hybrid test, Zhang et al. (2016) <doi:10.1016/j.jeconom.2016.02.017> is implemented which supports all of the individual tests in the package, e.g. Genest et al. (2009) <doi:10.1016/j.insmatheco.2007.10.005>. Estimation methods for the margins are provided and all the tests support parameter estimation and predefined values. The parameters are estimated by pseudo maximum likelihood but if it fails the estimation switches automatically to inversion of Kendall's tau. For reproducibility of results, the functions support the definition of seeds. Also all the tests support automatized parallelization of the bootstrapping tasks. The package provides an interface to perform new GoF tests by submitting the test statistic.