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Multivariate Dependence with Copulas
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.
Jun Yan <> and Ivan Kojadinovic <>, Marius Hofert <> and Martin Maechler <>
GPL (>= 3)