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doi:10.1016/0012-365X(95)00358-4 
Copyright © 1997 Published by Elsevier Science B.V.
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q-distributions and Markov processes
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Received 7 February 1995;
Abstract
We consider a sequence of integer-valued random variables Xn, n 
1, representing a special Markov process with transition probability λn, l, satisfying Pn, l = (1 − λn, l) Pn−1, l + λn, l−1 Pn−1, l−1. Whenever the transition probability is given by λn, l = qαn + βl + γ and λn, l = 1 − qαn+βl+γ, we can find closed forms for the distribution and the moments of the corresponding random variables, showing that they involve functions such as the q-binomial coefficients and the q-Stirling numbers. In general, it turns out that the q-notation, up to now mainly used in the theory of q-hypergeometrical series, represents a powerful tool to deal with these kinds of problems. In this context we speak therefore about q-distributions. Finally, we present some possible, mainly graph theoretical interpretations of these random variables for special choices of α, β and γ.
