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Infinitely divisible random transition probabilities with application to dependent Markov chains

Published online by Cambridge University Press:  17 February 2009

Peter L. Chesson
Peter L. Chesson
Affiliation:
Department of Zoology, The Ohio State University, 1735 Neil Avenue, Columbus, Ohio 43210, U.S.A.
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Abstract

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Random transition probability matrices with stationary independent factors define “white noise” environment processes for Markov chains. Two examples are considered in detail. Such environment processes can be used to construct several Markov chains which are dependent, have the same transition probabilities and are jointly a Markov chain. Transition rates for such processes are evaluated. These results have application to the study of animal movements.

Type
Research Article
Information
The ANZIAM Journal , Volume 25 , Issue 4 , April 1984 , pp. 463 - 472
Copyright
Copyright © Australian Mathematical Society 1984

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