<t>Thanks Aaron. Looks like an relatively easy job to fit the bivariate Poisson with the expressions you presented.I am also interested in possibilities to extend the model to incorporate more variables and have learned about the multivariate Poisson model. This model seems to be tricky to fit to da...

<t>Thanks Alan. To start with I log transformed the discrete variables before creating the correlation matrix and this did make a significant difference (for approach i mentioned above). I will look into a bivariate normal fitting as well. As I started googling on bivariate distributions I came acro...

<t>I have a dataset of two correlated poisson variablesX1 ~ Poisson(lambda1)X2 ~ Poisson(lambda2)Pr(X1,X2)<>Pr(X1)*Pr(X2)I would like to specify the joint distribution of X1 and X2 so that it fits a dataset.So far I have tried two things:i, created a correlation matrix for X1 and X2, cholesky decomp...

I would agree with you intution, check out Thorp's paper at page 6 where this is mentioned.http://www.bjmath.com/bjmath/thorp/ch2.pdf

In regard to my earlier posting, it is worth mentioning that I am associated with Codefarm.

<r>Codefarm, <URL url="http://www.codefarm.com">www.codefarm.com</URL>, offers a software that optimize CDO structures. It allows for user defined constraints, e.g. on diversification, correlation, attachment/detachment points and tranche ratings. It selects the names and notional that yields the be...