Hello,

I'm writing about msm. It may be that consistent users of Markov  models have a good idea as to what constitutes workable data for a model. I think of  general rules,  in basic statistical studies where n is limited to exclude fairly precise figures in the lower range. 
On the other hand Markov models don't seem to be often enough used for parameters to be as well laid out. 
I also get the feeling that msm is organized to work optimally with certain sizes and shapes of data. Is there a source that anyone is aware of on this? (I have the Nelder text on optimization, and also have a feeling that what's possible is pretty closely connected with optimization questions)

Thanks again,
Russell

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