Christophe Dutang <dutangc <at> gmail.com> writes:
Hello, I think what you need to look at is the log-likelihood. Something like sum
(log(dcopula(gumbelCopula(3),
x)). By the way, there is also the gumbel package available on CRAN where some
classic fitting methods are available.
Regards Christophe Le 9 nov. 2010 ? 22:20, salmajj <at> softhome.net a ?crit :
Hi I tried a lot of time to send this message hope it works this time! Hi everybody, my objective is to find the corresponding parameter of the gumbel copula
that best fit my empirical
dependancy structure. i.e I already know that the gumbel copula is the best
family but i want to decide on
the best parameter ?
in other words let x <- rcopula(gumbelCopula(3), 100) suppose we do not know that alpha=3 is the right value and we are
wondering if the gumbel copula with alpha
equal to 2 is a good fit
let test : gofEVCopula(gumbelCopula(2), x) this returns Parameter estimate(s): 3.044912 Cramer-von Mises statistic: 0.0004143588 with p-value 0.8616384 let test : gofEVCopula(gumbelCopula(3), x) this returns: arameter estimate(s): 3.044912 Cramer-von Mises statistic: 0.0004143588 with p-value 0.8556444 So if I well understand this function gofCopula only indicate that the
gumbel family is a good fit and we can
not decide on the best parameter of the gumbel copula as the results were
the same!
So which test we could use to know that actually the gumbal copula with
parameter 3 and not 2 fit best the dependancy?
Thanks a lot!
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-- Christophe Dutang Ph.D. student at ISFA, Lyon, France website: http://dutangc.free.fr
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!