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)
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.
Value
A numeric vector of the bivariate copula distribution function evaluated at u1 and u2.
# simulate from a bivariate Claytonsimdata <- BiCopSim(300, 3, 3.4)
# evaluate the distribution function of the bivariate t-copulau1 <- simdata[,1]
u2 <- simdata[,2]
BiCopCDF(u1, u2, 3, 3.4)