indepCopula

Constructs an independence copula class object with its corresponding
  dimension.

multivariate

distribution

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.

indepCopula: Construction of independence copula class objects

Description

Usage

Arguments

Value

See Also

Examples