[R-SIG-Finance] Copula and Multivariate distribution

Christophe Dutang dutangc at gmail.com
Thu Jan 20 07:57:39 CET 2011


you can use something like that

eqf <- function(x, sampleMarg) as.numeric(quantile(sampleMarg, probs=x))

and apply eqf on each marginal after the copula fit if you want to generate random samples or directly ecdf if you want to compute multivariate distribution function.


Christophe Dutang
Ph.D. student at ISFA, Lyon, France
website: http://dutangc.free.fr

Le 19 janv. 2011 à 21:50, salmajj a écrit :

> Hi all, 
> I understand that rmvdc generates random number from mvdc object. But the
> mvdc object can only be used if we define the marginals! So my question is
> suppose we don't find any distribution which fit marginals so we use the
> Canonical Maximum Likelihood method (This approach uses the empirical CDF of
> each marginal distribution to transform the observations into pseudo
> observations with uniform margins) SO after finding the copula which fit the
> dependancy HOW i can generate random number which mimic the data? 
> Hope my question is clear, please if someone have an idea help me! 
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