Multivariate Dependence with Copulas
Description
Classes (S4) of commonly used copulas including elliptical
(normal and t), Archimedean (Clayton, Gumbel, Frank, and
Ali-Mikhail-Haq), extreme value (Gumbel, Husler-Reiss,
Galambos, Tawn, and t-EV), and other families (Plackett and
Farlie-Gumbel-Morgenstern). Methods for density, distribution,
random number generation, bivariate dependence measures,
perspective and contour plots. Functions for fitting copula
models with variance estimate. Independence tests among random
variables and random vectors. Serial independence tests for
univariate and multivariate continuous time series.
Goodness-of-fit tests for copulas based on multipliers, the
parametric bootstrap with several transformation options.
Bivariate and multivariate tests of extreme-value dependence.
Bivariate tests of exchangeability. Now with former 'nacopula'
for working with nested Archimedean copulas. Specifically,
providing procedures for computing function values and cube
volumes, characteristics such as Kendall's tau and tail
dependence coefficients, efficient sampling algorithms, various
estimators, and goodness-of-fit tests. The package also
contains related univariate distributions and special functions
such as the Sibuya distribution, the polylogarithm, Stirling
and Eulerian numbers.