>>>>> Steven Yen
>>>>> on Tue, 7 Nov 2023 09:09:33 +0800 writes:
> Dear
> I estimate a sample selection model using the Clayton copula and Burr
> and Gaussian marginal. I need to derive ther Kendall'sw tau from the
> concordance coefficient by integration. I came across a way to do that
> in R long time ago but cannot find it again. Can somewone tell me what
> to read and what to use? Thank you.
> Steven Yen
I think you can estimate your model relatively easily using our
package {copula} and the function fitMvdc()
https://search.r-project.org/CRAN/refmans/copula/html/fitMvdc.html
MVDC := Multivariate Variate Distribution {built from} Copula
To solve the question you asked --- but would not need to answer if
using fitMvdc(),
you can use e.g.,
> iTau(claytonCopula(), tau = 1.4)
[1] -7
or look up the formulas for tau() or its inverse 'iTau':
> copClayton@tau
function (theta)
{
theta/(theta + 2)
}
> copClayton@iTau
function (tau)
{
2 * tau/(1 - tau)
}
>
Best regards,
Martin
{and yes, consider getting our 'useR! Springer series book, as
it's the only "real" book, I've been a coauthor..
https://copula.r-forge.r-project.org/book/ }
--
Martin Maechler
ETH Zurich and R Core team
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
