Copula in R

Hi there,

Suppose you have produced 15 CDFs, which all lie between [0,1]. They are pseudo samples to be fitted in the copula model.

There are some packages in R allow you to estimate the parameters in copula function, for example, "copula", "QRMlib".....

Your marginals have been estimated by GPD model, which means you will adopt two-step IFM method for copula estimation.

Alternatively, you can use CML method, which use empirical distribution for the marginals. For this, the function "edf" can help you to produce all your return data into uniform variates.

Hope this helps.

Regards,
Michael



-----Original Message-----
From: r-sig-finance-bounces at stat.math.ethz.ch
[mailto:r-sig-finance-bounces at stat.math.ethz.ch]On Behalf Of Yana Roth
Sent: 2009??1??30?? 14:37
To: r-sig-finance at stat.math.ethz.ch
Subject: [R-SIG-Finance] Copula in R


Hello,
I try to reproduce copula fitting from Matlab by R. I constructed pieswise distribution: Generalised Pareto at the tails and empirical distribution estimated with Gaussian Kernel. Like this I obtain 15 CDF. However, I dont find my way to convert them to uniforms and fit copula.
?
If you could provide some help, I would be thanjful
?
Thank You
Yana

The QRMlib function "fit.tcopula.rank" with method="kendall" will accept
 the uniform data from the cdf transformation.

It is more commonplace to first filter the data with a process like
garch, and then apply the fit to the standardized residuals.

There is also a package on r-forge for the semi-parametric distribution
with pareto tail which implements density, distribution, quantile and
sampling (http://r-forge.r-project.org/projects/spd/).

-Alexios

Hello,
I try to reproduce copula fitting from Matlab by R. I constructed pieswise distribution: Generalised Pareto at the tails and empirical distribution estimated with Gaussian Kernel. Like this I obtain 15 CDF. However, I dont find my way to convert them to uniforms and fit copula.
 
If you could provide some help, I would be thanjful
 
Thank You
Yana


      
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