[R] mixture model of binned data

[D L Rustvold]

Is there a ready means to do mixture models of binned data in R?

I have a two dimensional grid of intensity values that represents many 
individual observations that are known to have bivariate normal 
distributions, although there is frequent overlap between the 
distributions.  There is also a degree of noise in the data that may be 
modeled by a poisson distribution.  I am looking for a way to identify 
the mixture model that best describes a subset of this grid of 
intensities so that I can deconvolute the multiple observations and 
noise distributions for quantification purposes.

I thought Mclust might be of use, but I didn't see any support for 
binned data.  I have searched the archives, read the FAQ, and the 
document "Fitting Distributions with R" without finding a successful 
solution.

Any help would be appreciated.

Cheers,
Leif Rustvold