Copula function in multivariate dependency analysis - Maple Application Center
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## Copula function in multivariate dependency analysis

Author
: I. Hlivka
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Copula is a constructor function for multivariate distribution from univariate marginals. It is a method to link univariate samples, not necessarily from identical distributions, into joint multivariate distributions.  In this way, copulas are more generic and flexible functions to study dependency arising from multivariate distributions.

Conceptually, copulas are based on transformation of the underlying marginal into new derived variable with uniform distribution. Consequently, any multivariate distribution can be expressed in the form of copula function. If each marginal is continuous then copula is unique. Sklar in 1959 was the first to point this out.

Copulas represent a broad set of functions and they generally differ by (i) number of dependency factors and (ii) construction complexity. The choose of copula depends on the nature of the multivariate study and fitting objectives to an underlying data.

#### Application Details

Publish Date: December 29, 2010
Created In: Maple 14
Language: English

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statistics statistics modeling