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A Compound Poisson Approximation Inequality

Published online by Cambridge University Press:  14 July 2016

Erol A. Peköz*
Affiliation:
Boston University
*
Postal address: School of Management, Boston University, 595 Commonwealth Avenue, Boston, MA 02215, USA. Email address: [email protected]
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Abstract

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We give conditions under which the number of events which occur in a sequence of m-dependent events is stochastically smaller than a suitably defined compound Poisson random variable. The results are applied to counts of sequence pattern appearances and to system reliability. We also provide a numerical example.

Type
Short Communications
Copyright
© Applied Probability Trust 2006 

References

Aldous, D. J. (1989). Probability Approximations via the Poisson Clumping Heuristic. Springer, New York.CrossRefGoogle Scholar
Arratia, R., Goldstein, L. and Gordon, L. (1989). Two moments suffice for Poisson approximations: the Chen–Stein method. Ann. Prob. 17, 925.CrossRefGoogle Scholar
Barbour, A. D. and Månsson, M. (2002). Compound Poisson process approximation. Ann. Prob. 30, 14921537.Google Scholar
Barbour, A. D. and Chryssaphinou, O. (2001). Compound Poisson approximation: a user's guide. Ann. Appl. Prob. 11, 9641002.Google Scholar
Barbour, A. D., Holst, L. and Janson, S. (1992). Poisson Approximation. Oxford University Press.CrossRefGoogle Scholar
Chang, G. J., Cui, L. and Hwang, F. K. (2000). Reliabilities of Consecutive-k Systems (Network Theory Appl. 4). Kluwer, Dordrecht.Google Scholar
Chryssaphinou, O. and Papastavridis, S. (1988). A limit theorem on the number of overlapping appearances of a pattern in a sequence of independent trials. Prob. Theory Relat. Fields 79, 129143.Google Scholar
Chryssaphinou, O., Papastavridis, S. and Vaggelatou, E. (2001). Poisson approximation for the non-overlapping appearances of several words in Markov chains. Combin. Prob. Comput. 10, 293308.CrossRefGoogle Scholar
Erhardsson, T. (2000). Compound Poisson approximation for counts of rare patterns in Markov chains and extreme sojourns in birth–death chains. Ann. Appl. Prob. 10, 573591.Google Scholar
Geske, M. X. et al. (1995). Compound Poisson approximation for word patterns under Markovian hypotheses. J. Appl. Prob. 32, 877892.Google Scholar
Klass, M. J. and Nowicki, K. (2003). An optimal bound on the tail distribution of the number of recurrences of an event in product spaces. Prob. Theory Relat. Fields 126, 5160.Google Scholar
Le Cam, L. (1960). An approximation theorem for the Poisson binomial distribution. Pacific J. Math. 10, 11811197.CrossRefGoogle Scholar
Peköz, E. A. (1996). Stein's method for geometric approximation. J. Appl. Prob. 33, 707713.Google Scholar
Peköz, E. A. and Ross, S. M. (1995). A simple derivation of exact reliability formulas for linear and circular consecutive-k-of-n:F systems. J. Appl. Prob. 32, 554557.Google Scholar
Peköz, E. A. and Ross, S. M. (2004). Compound random variables. Prob. Eng. Inf. Sci. 18, 473484.CrossRefGoogle Scholar
Von Mises, R. (1921). Das Problem der Iterationen. Z. Angew. Math. Mech. 1, 298307.CrossRefGoogle Scholar