- 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