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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