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An invariant of representations of phase-type distributions and some applications

Published online by Cambridge University Press:  14 July 2016

C. Commault*
Affiliation:
Laboratoire d 'Automatique de Grenoble
J. P. Chemla*
Affiliation:
Laboratoire d 'Automatique de Grenoble
*
Postal address: Laboratoire d 'Automatique de Grenoble, ENSIEG/INPG, BP 46, 38402 Saint Martin d'Hères, France. e-mail:commault@lag.grenet.fr
Postal address: Laboratoire d 'Automatique de Grenoble, ENSIEG/INPG, BP 46, 38402 Saint Martin d'Hères, France. e-mail:commault@lag.grenet.fr

Abstract

In this paper we consider phase-type distributions, their Laplace transforms which are rational functions and their representations which are finite-state Markov chains with an absorbing state. We first prove that, in any representation, the minimal number of states which are visited before absorption is equal to the difference of degree between denominator and numerator in the Laplace transform of the distribution. As an application, we prove that when the Laplace transform has a denominator with n real poles and a numerator of degree less than or equal to one the distribution has order n. We show that, in general, this result can be extended neither to the case where the numerator has degree two nor to the case of non-real poles.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1996 

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References

[1] Botta, R. F., Harris, C. M. and Marshal, W. G. (1987) Characterisation of generalized hyperexponential distribution functions. Commun. Stat.-Stoch. Models 3, 115148.Google Scholar
[2] Commault, C. and Chemla, J. P. (1993) On dual and minimal phase-type representations. Commun. Stat.-Stoch. Models 9, 421434.Google Scholar
[3] Cox, D. R. (1955) A use of complex probabilities in the theory of stochastic processes. Proc. Camb. Phil. Soc. 51, 313319.CrossRefGoogle Scholar
[4] Cummani, A. (1982) On the canonical representation of homogeneous Markov processes modelling failure-time distributions. Microelect. Reliab. 22, 583602.Google Scholar
[5] Iversen, V. B. and Nielsen, B. F. (1985) Some properties of Coxian distributions with applications. Colloq. Modélisation et outils de performances, Sophia Antipolis. pp. 6974.Google Scholar
[6] Neuts, M. F. (1981) Matrix Geometric Solutions in Stochastic Models: An Algorithmic Approach. The Johns Hopkins University Press, Baltimore.Google Scholar
[7] O'Cinneide, C. A. (1989) On non-uniqueness of representations of phase-type distributions. Commun. Stat.-Stock Models 5, 247259.Google Scholar
[8] O'Cinneide, C. A. (1990) Characterization of phase-type distributions. Commun. Stat.-Stock Models 6, 157.Google Scholar
[9] O'Cinneide, C. A. (1991) Phase-type distributions and invariant polytopes. Adv. Appl. Prob. 23, 515535.Google Scholar
[10] O'Cinneide, C. A. (1993) Order and triangular order of phase-type distributions. Commun. Stat.-Stoch. Models 9, 508531.Google Scholar
[11] Ramaswami, V. (1990) A duality theorem for matrix paradigms in queueing theory. Commun. Stat.-Stoch. Models 6, 163167.Google Scholar