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Random sums stopped by a rare event : a new approximation

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Języki publikacji
EN
Abstrakty
EN
The convergence of a geometric sum of positive i.i.d. random variables to an exponential distribution is a well-known result. This convergence provided various and useful approximations in reliability, queueing or risk theory. However, for concrete applications, this exponential approximation is not sharp enough for small values of mission time. So, other approximations have been proposed (Bon and Pamphile (2001), Kalashnikov (1997)). In this paper we propose a new point of view where the exponential approximation appears as a first-order approximation. We consider more general random sums stopped by a rare event, where summands are no more assumed to be independent neither nonnegative. So we give a second-order approximation. As illustration we consider stopping time with negative binomial distribution. This approximation provides a new evaluation tool in reliability analysis of highly reliable systems. The accuracy of this approximation is studied numerically.
Słowa kluczowe
Rocznik
Strony
237--252
Opis fizyczny
Bibliogr. 16 poz., wykr.
Twórcy
autor
  • University Paul Sabatier, Department of Probability and Statistics, 118 route de Narbonne, F-31062 Toulouse Cedex, France
autor
  • University Paris Sud, Department of Mathematics, Bat 425, F-91405 Orsay Cedex, France
Bibliografia
  • [1] J. Adell and J. De La Cal, Approximating gamma distributions by normalized binomial distributions, J. Appl. Probab. 31 (1994), pp. 391-400.
  • [2] S. Asmussen, Applied Probability and Queues, Wiley, 1987.
  • [3] P. Billingsley, Convergence in Probability Measures, Wiley, 1968.
  • [4] J.-L. Bon and P. Pamphile, Pessimistic approximation of the reliability for regenerative models, Markov Process. Related. Fields 7 (2001), pp. 491-502.
  • [5] M. Brown, Error bounds for exponential approximations of geometric convolutions, Ann. Probab. 18 (1990), pp. 1388-1402.
  • [6] M. Casalis, The 2d+4 simple quadratic natural exponential families on d, Ann. Statist. 24 (1996), pp. 1828-1854.
  • [7] D. Dacunha-Castelle and M. Duflo, Probabilités et statistiques, Vol. 2, Masson, 1983.
  • [8] G. Doetsch, Introduction to the Theory and Application of the Laplace Transformation, Springer, New York-Heidelberg 1974.
  • [9] M. Duflo, Random Iterative Models, Springer, 1997.
  • [10] J. Engel and M. Zijlstra, A characterization of the gamma distribution by the negative binomial distribution, J. Appl. Probab. 17 (1980), pp. 1138-1144.
  • [11] W. Feller, An Introduction to Probability Theory and Its Applications, Vol. 2, Wiley, 1971.
  • [12] I. Gertsbakh, Asymptotic methods in reliability theory: A review, Adv. in Appl. Probab. 16 (1984), pp. 147-175.
  • [13] J. Grandell, Mixed Poisson Process, Chapman & Hall, London 1997.
  • [14] V. Kalashnikov, Geometric Sums: Bounds for Rare Events with Applications, Kluwer Academic Publishers, 1997.
  • [15] V. Kruglov and V. Korolev, Limiting behavior of sums of a random number of random variables, Probab. Theory Appl. 36 (1991), pp. 792-794.
  • [16] V. Seshadri, The Inverse Gaussian Distribution, Clarendon Press, Oxford 1993.
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-fa12b0fe-ee76-4fbe-886b-6563e192d4c7
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