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

  • Yasushi Masuda (a1) and Ushio Sumita (a2)
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.

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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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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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Journal of Applied Probability
  • ISSN: 0021-9002
  • EISSN: 1475-6072
  • URL: /core/journals/journal-of-applied-probability
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