- statistics: p = copulacdf (family, x, theta)
- statistics: p = copulacdf ('t', x, theta, df)
 Copula family cumulative distribution functions (CDF).
 
Arguments
 
- 
 family is the copula family name. Currently, family can
 be 'Gaussian'for the Gaussian family,'t'for the
 Student’s t family,'Clayton'for the Clayton family,'Gumbel'for the Gumbel-Hougaard family,'Frank'for
 the Frank family,'AMH'for the Ali-Mikhail-Haq family, or'FGM'for the Farlie-Gumbel-Morgenstern family.
- 
 x is the support where each row corresponds to an observation.
 
- 
 theta is the parameter of the copula. For the Gaussian and
 Student’s t copula, theta must be a correlation matrix. For
 bivariate copulas theta can also be a correlation coefficient.
 For the Clayton family, the Gumbel-Hougaard family, the Frank family,
 and the Ali-Mikhail-Haq family, theta must be a vector with the
 same number of elements as observations in x or be scalar. For
 the Farlie-Gumbel-Morgenstern family, theta must be a matrix of
 coefficients for the Farlie-Gumbel-Morgenstern polynomial where each
 row corresponds to one set of coefficients for an observation in
 x. A single row is expanded. The coefficients are in binary
 order.
 
- 
 df is the degrees of freedom for the Student’s t family.
 df must be a vector with the same number of elements as
 observations in x or be scalar.
 
Return values
 
- 
 p is the cumulative distribution of the copula at each row of
 x and corresponding parameter theta.
 
Examples
 |  |    x = [0.2:0.2:0.6; 0.2:0.2:0.6];
 theta = [1; 2];
 p = copulacdf ("Clayton", x, theta)
 
   x = [0.2:0.2:0.6; 0.2:0.1:0.4];
 theta = [0.2, 0.1, 0.1, 0.05];
 p = copulacdf ("FGM", x, theta)
   | 
 
References
 
- 
 Roger B. Nelsen. An Introduction to Copulas. Springer,
 New York, second edition, 2006.
 
 See also: 
  copulapdf, 
  copularnd
Source Code: 
  copulacdf