VineCopula (version 1.6-1)

BiCopCDF: Distribution Function of a Bivariate Copula

Description

This function evaluates the cumulative distribution function (CDF) of a given parametric bivariate copula.

Usage

BiCopCDF(u1, u2, family, par, par2 = 0, obj = NULL)

Arguments

u1,u2

Numeric vectors of equal length with values in [0,1].

family

An integer defining the bivariate copula family: 0 = independence copula 1 = Gaussian copula 3 = Clayton copula 4 = Gumbel copula 5 = Frank copula 6 = Joe copula 7<

par

Copula parameter.

par2

Second parameter for bivariate copulas with two parameters (t, BB1, BB6, BB7, BB8, Tawn type 1 and type 2; default: par2 = 0). par2 should be an positive integer for the Students's t copula family = 2.

obj

BiCop object containing the family and parameter specification.

Value

• A numeric vector of the bivariate copula distribution function evaluated at u1 and u2.

Details

If the family and parameter specification is stored in a BiCop object obj, the alternative version BiCopCDF(u1, u2, obj) can be used.

See Also

BiCopPDF, BiCopHfunc, BiCopSim, BiCop

Examples

## simulate from a bivariate Clayton
simdata <- BiCopSim(300, 3, 3.4)

## evaluate the distribution function of the bivariate Clayton copula
u1 <- simdata[,1]
u2 <- simdata[,2]
BiCopCDF(u1, u2, 3, 3.4)

## estimate a bivariate copula from the data and evaluate its CDF 
cop <- BiCopSelect(u1, u2)
BiCopCDF(u1, u2, cop)