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copulacdf

Copula cumulative distribution function

Syntax

Y = copulacdf('Gaussian',U,rho)
Y = copulacdf('t',U,rho,NU)
Y = copulacdf('family',U,alpha)

Description

Y = copulacdf('Gaussian',U,rho) returns the cumulative probability of the Gaussian copula with linear correlation parameters rho, evaluated at the points in U. U is an n-by-p matrix of values in [0,1], representing n points in the p-dimensional unit hypercube. rho is a p-by-p correlation matrix. If U is an n-by-2 matrix, rho may also be a scalar correlation coefficient.

Y = copulacdf('t',U,rho,NU) returns the cumulative probability of the t copula with linear correlation parameters rho and degrees of freedom parameter NU, evaluated at the points in U. U is an n-by-p matrix of values in [0,1]. rho is a p-by-p correlation matrix. If U is an n-by-2 matrix, rho may also be a scalar correlation coefficient.

Y = copulacdf('family',U,alpha) returns the cumulative probability of the bivariate Archimedean copula determined by family, with scalar parameter alpha, evaluated at the points in U. family is Clayton, Frank, or Gumbel. U is an n-by-2 matrix of values in [0,1].

Examples

expand all

Compute the Gaussian Copula cdf

Compute and plot the cdf of a Gaussian copula.

u = linspace(0,1,10);
[U1,U2] = meshgrid(u,u);
F = copulacdf('Clayton',[U1(:) U2(:)],1);
surf(U1,U2,reshape(F,10,10))
xlabel('u1')
ylabel('u2')

See Also

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