[R] using MCLUST package to estimate a poisson-gaussian process

From: Tessa Discage <tessadiscage.ny_at_gmail.com>
Date: Thu, 12 Jun 2008 16:01:51 -0400

 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?



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