Hi all,
I am trying to find a formula for the variances in the long-run
probabilities associated with a Markov process (finite-state,
discrete-time, positive, recurrent, aperiodic). Specifically, what I want
to know is this: if a large number of individuals' transitions between
states were governed by a Markov process, then, in the long run, the
fraction of individuals expected in each state would be given by the
limiting distribution. What are the variances associated with those fractions?
Ideally, I would also like to project the variance iteratively for
transient distributions as well, i.e., from a given initial distribution
until the limiting distribution is reached.
I've had no luck with stochastic processes texts, or on the internet. I'd
be grateful if anyone can direct me to a book or paper indicating how these
quantities can be calculated. Thanks in advance.
Regards,
Sean
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Sean R. Connolly, PhD
Department of Marine Biology
James Cook University
Townsville, QLD 4811
AUSTRALIA
Ph: 61 7 4781 4242
Fax: 61 7 4725 1570
http://www.jcu.edu.au/school/mbiolaq/mbiol/staff/sconnolly.html#SConnolly
VISIT THE NEW CENTRE FOR CORAL REEF BIODIVERSITY
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