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First passage times and lumpability of semi-Markov processes

Published online by Cambridge University Press:  14 July 2016

Ushio Sumita
Affiliation:
University of Rochester
Maria Rieders
Affiliation:
University of Rochester

Abstract

A necessary and sufficient condition of Serfozo (1971) for lumpability of semi-Markov processes is reinterpreted in terms of first-exit times. Furthermore, a new necessary and sufficient condition is developed by establishing relationships between first-passage times and lumpability of semi-Markov processes. The approach taken in this paper is entirely based on the Laplace-transform domain.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1988 

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Footnotes

This paper has been partially supported by the IBM Program of Support for Education in the Management of Information Systems and by NSF Grant ECS-8600992.

References

[1] Abdel-Moneim, A. M. and Leysieffer, F. W. (1982) Weak lumpability in finite Markov chains. J. Appl. Prob. 19, 685691.Google Scholar
[2] Barr, D. R. and Thomas, M. U. (1977) An eigenvector condition for Markov chain lumpability. Operat. Res. 25, 10281031.Google Scholar
[3] Burke, C. and Rosenblatt, M. (1958) A Markovian function of a Markov chain. Ann. Math. Statist. 29, 11121122.Google Scholar
[4] Cinlar., E. (1966) Decomposition of a semi-Markov process under a Markovian rule. Austral. J. Statist. 8, 163170.Google Scholar
[5] Cinlar, E. (1967) Decomposition of a semi-Markov process under a state dependent rule. SIAM J. Appl. Math. 15, 252263.Google Scholar
[6] Cinlar, E. (1969) Markov renewal theory. Adv. Appl. Prob. 1, 123187.Google Scholar
[7] Çinlar, E. (1975) Markov renewal theory: A survey. Management Sci. 21, 727752.Google Scholar
[8] Dynkin, E. (1965) Markov Processes I. Springer-Verlag, Berlin.Google Scholar
[9] Keilson, J. (1979) Markov Chain ModelsRarity and Exponentiality . Springer-Verlag, New York.CrossRefGoogle Scholar
[10] Kemeny, J. and Snell, L. (1969) Finite Markov Chains. Van Nostrand, Princeton, NJ.Google Scholar
[11] Rosenblatt, M. (1959) Functions of a Markov process that are markovian. J. Math. Mech. 8, 585596.Google Scholar
[12] Rosenblatt, M. (1962) Random Processes. Oxford University Press, New York.Google Scholar
[13] Serfozo, R. F. (1969) Time and Space Transformations of Semi-Markov Processes. Doctoral Thesis in Applied Mathematics, Northwestern University.Google Scholar
[14] Serfozo, R. F. (1971) Functions of semi-Markov processes. SIAM J. Appl. Math. 20, 530535.CrossRefGoogle Scholar
[15] Sumita, U. and Masuda, Y. (1987) An alternative approach to the analysis of finite semi-Markov and related processes. Stoch. Models 3, 6787.Google Scholar
[16] Thomas, M. U. and Barr, D. R. (1977) An approximate test of Markov chain lumpability. J. Amer. Statist. Assoc. 72, 175179.CrossRefGoogle Scholar