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A multivariate reward process defined on a semi-Markov process and its first-passage-time distributions

Published online by Cambridge University Press:  14 July 2016

Yasushi Masuda and
Ushio Sumita
Yasushi Masuda*
Affiliation:
University of California, Riverside
Ushio Sumita*
Affiliation:
University of Rochester
*
∗Postal address: Graduate School of Management, University of California, Riverside, CA 92521, USA.
∗∗Postal address: Simon Graduate School of Business Administration. University of Rochester, Rochester, NY 14627, USA.
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Abstract

A multivariate reward process defined on a semi-Markov process is studied. Transform results for the distributions of the multivariate reward and related processes are derived through the method of supplementary variables and the Markov renewal equations. These transform results enable the asymptotic behavior to be analyzed. A class of first-passage time distributions of the multivariate reward processes is also investigated.

Keywords

ASYMPTOTIC ANALYSISFIRST-PASSAGE TIME DISTRIBUTIONS

Information

Type
Research Papers
Information
Journal of Applied Probability , Volume 28 , Issue 2 , June 1991, pp. 360 - 373
Copyright
Copyright © Applied Probability Trust 1991 

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Footnotes

Partially supported by IBM Program of Support for Education in the Management of Information Systems, NSF Grant ECS-8600992, and Nippon Telegraph and Telephone Corporation.

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