R help - Jun 2008 - using MCLUST package to estimate a poisson-gaussian process

Hi All,
I am using em() function to estimate a poisson-gaussian process from a
univariate one dimension time series, but not sure how to do. In the help
manual, it specify that in "pro" of the argument
"parameter", if the model
includes a Poisson term for noise, there should be one more mixing
proportion than the number of Gaussian components. But in the example, the
parameter is specified by mstep() function, while the mstep() function says
for arguement "z", in analyses involving noise, this should not
include the
conditional probabilities for the noise component.
I am confused...
Also how to specify the model-specified parameters in the em() function
besides just mean and variance? what if i want to estimate the mean
reverting speed??
Can anyone share the experience of using MCLUST package to estimate
poisson-gaussian process?

THanks!

Tessa

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