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 and on
the parametric bootstrap. 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.