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Estimation of transition probabilities in a multiparticle semi-Markov system

Published online by Cambridge University Press:  14 July 2016

David Burman*
Affiliation:
Bell Telephone Laboratories, Holmdel, New Jersey

Abstract

Particles enter a finite-state system and move according to independent sample paths from a semi-Markov process. Strong limit theorems are developed for the ratio of the flow of particles from states i to j and the flow out of When the cumulative arrival of particles into the system up to time t, A (t) ∼ λtα, then a.s. When A (t)∼ λekt, then the flow between states must be normalized by the Laplace–Stieltjes transform of the conditional holding time distribution, in order to make the ratio an unbiased estimator of ρij.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1976 

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References

Cox, D. R. (1962) Renewal Theory. Methuen, London.Google Scholar
Lewinski, D. A. (1967) A model for analyzing telephone costs. Presented at the Thirty-Second National Meeting of the Operations Research Society, Chicago.Google Scholar
Pyke, R. (1961) A Markov-renewal process with finitely many states. Ann. Math. Statist. 32, 12431259.CrossRefGoogle Scholar
Widder, D. (1941) The Laplace Transform. Princeton University Press.Google Scholar