genFun

genFun-methods

genFun,claytonCopula-method

genFun,frankCopula-method

genFun,gumbelCopula-method

genFun,amhCopula-method

genInv

genInv-methods

genInv,claytonCopula-method

genInv,frankCopula-method

genInv,gumbelCopula-method

genInv,amhCopula-method

genFunDer1

genFunDer1-methods

genFunDer1,claytonCopula-method

genFunDer1,frankCopula-method

genFunDer1,gumbelCopula-method

genFunDer1,amhCopula-method

genFunDer2

genFunDer2-methods

genFunDer2,claytonCopula-method

genFunDer2,frankCopula-method

genFunDer2,gumbelCopula-method

genFunDer2,amhCopula-method

Afun

Afun-methods

Afun,galambosCopula-method

Afun,gumbelCopula-method

Afun,huslerReissCopula-method

Afun,tawnCopula-method

Afun,tevCopula-method

Afun,asymCopula-method

Afun,indepCopula-method

AfunDer

AfunDer-methods

AfunDer,galambosCopula-method

AfunDer,gumbelCopula-method

AfunDer,huslerReissCopula-method

AfunDer,tawnCopula-method

AfunDer,tevCopula-method

an object of class <code>"<links4class>copula</links4class>"</code>.

copula

numerical vector at which these functions are to be
    evaluated.

u, s, w

Methods to evaluate the generator function, the inverse generator
 function, and derivatives of the generator function.

multivariate

methods

generator

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.

Martin Maechler

Multivariate Dependence with Copulas

generator function

Generator functions for Archimedean and extreme value copulas

generator: Generator functions for Archimedean and extreme value copulas

Description

Usage

Arguments

Details