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Sunday, 9 July 2006

pr.probability - Is there a way to analytically compute the recurrence time of a finite Markov process?

This is a response to a comment.



The coupon collector's problem is elementary. I don't have a particular scholarly reference in mind, but rather the technique of the proofs. There are a few proofs of the nHn expected time to collect all coupons. One possibility is that you can compute the expected time to collect the kth new coupon,
n/(nk+1). That uses a lot of symmetry you don't have for a general Markov process. Here, you have transition probabilities and times on (current location, subset visited so far).



Analogous to what I did here, you can use inclusion-exclusion. The expected time to cover everything (with discrete time) is the sum of the probability that you haven't covered everything by time t1, which you can express as



sumtsumSsubsetV1|S|+1Prob(XiilttcapS=emptyset)



where V = 1,...,n. You can switch the order of summation to get about 2n analytically solvable problems about avoiding particular subsets.



sumSsubsetV1|S|+1A(S)



where A(S) = expected time before you first enter S.



The same holds for continuous time.

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