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Randomization of intensities in a Markov chain

Published online by Cambridge University Press:  01 July 2016

M. Yadin and
R. Syski
M. Yadin*
Affiliation:
Technion-Israel Institute of Technology
R. Syski*
Affiliation:
University of Maryland
*
∗ Postal address: Faculty of Industrial and Management Engineering, Technion—Israel Institute of Technology, Haifa, Israel.
∗∗ Permanent address: Department of Mathematics, University of Maryland, College Park. Maryland 20742, U.S.A. When this paper was written this author was Pinhas Naor Visiting Professor at the Faculty of Industrial and Management Engineering, Technion—Israel Institute of Technology, on leave from the University of Maryland.
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Abstract

The matrix of intensities of a Markov process with discrete state space and continuous time parameter undergoes random changes in time in such a way that it stays constant between random instants. The resulting non-Markovian process is analyzed with the help of supplementary process defined in terms of variations of the intensity matrix. Several examples are presented.

Keywords

BACKWARD EQUATIONINTENSITIESMARKOV CHAINSNON-HOMOGENEOUS CHAINSRANDOMIZATIONTWO-DIMENSIONAL CHAIN

Information

Type
Research Article
Information
Advances in Applied Probability , Volume 11 , Issue 2 , June 1979, pp. 397 - 421
Copyright
Copyright © Applied Probability Trust 1979 

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References

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