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Performance Analysis with Truncated Heavy-Tailed Distributions

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An Erratum to this article was published on 01 March 2006

Abstract

This paper deals with queues and insurance risk processes where a generic service time, resp. generic claim, has the form UK for some r.v. U with distribution B which is heavy-tailed, say Pareto or Weibull, and a typically large K, say much larger than \(\mathbb{E}U\). We study the compound Poisson ruin probability ψ(u) or, equivalently, the tail \(\mathbb{P}{\left( {W > u} \right)}\) of the M/G/1 steady-state waiting time W. In the first part of the paper, we present numerical values of ψ(u) for different values of K by using the classical Siegmund algorithm as well as a more recent algorithm designed for heavy-tailed claims/service times, and compare the results to different approximations of ψ(u) in order to figure out the threshold between the light-tailed regime and the heavy-tailed regime. In the second part, we investigate the asymptotics as K → ∞ of the asymptotic exponential decay rate γ = γ (K) in a more general truncated Lévy process setting, and give a discussion of some of the implications for the approximations.

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References

  • S. Asmussen, Ruin Probabilities, World Scientific: Singapore, 2000.

    Google Scholar 

  • S. Asmussen, Applied Probability and Queues, Springer-Verlag: New York, 2003.

    MATH  Google Scholar 

  • S. Asmussen, and D. P. Kroese, “Improved algorithms for rare event simulation with heavy tails,” Submitted to J. Appl. Probability (Pending revision), 2004.

  • S. Asmussen, and M. Pihlsgård, “Performance analysis with truncated heavy-tailed distributions,” MaPhySto Research Report 24-2004, 2004. Extended version of the current article.

  • S. Asmussen, and R. Y. Rubinstein, “Steady-state rare events simulation in queueing models and its complexity properties,” In J. Dshalalow (ed.), Advances in Queueing: Models, Methods and Problems, pp. 429–466, CRC Press: Boca Raton, 1995.

    Google Scholar 

  • S. Asmussen, K. Binswanger, and B. Højgaard, “Rare events simulation for heavy-tailed distributions,” Bernoulli vol. 6 pp. 303–322, 2000.

    Article  MathSciNet  MATH  Google Scholar 

  • N. H. Bingham, C. M. Goldie, and J. L. Teugels, Regular Variation, Cambridge University Press: Cambridge, 1987.

    MATH  Google Scholar 

  • P. Embrechts, C. Klüppelberg, and T. Mikosch, Modeling Extremal Events for Finance and Insurance, Springer-Verlag: New York, 1997.

    Google Scholar 

  • W. Feller, An Introduction To Probability Theory and Its Applications, Volume 2, John Wiley and Sons: New York, 1970.

    Google Scholar 

  • P. Heidelberger, “Fast simulation of rare events in queueing and reliability models,” ACM TOMACS vol. 6 pp. 43–85, 1995.

    Article  Google Scholar 

  • C. Hipp, “Speedy Panjer for phase-type claims,” Insurance: Mathematics and Economics (to appear), 2004.

  • P. R. Jelenković, “Network multiplexer with truncated heavy-tailed arrival streams,” In Proceedings of the IEEE INFOCOM'99, http://www.ieee-infocom.org/1999/papers/05_b02.pdf, 1999a.

  • P. R. Jelenković, “Subexponential loss rates in a GI/GI/1 queue with applications,” Queueing Systems vol. 33 pp. 91–123, 1999b.

    Article  MATH  Google Scholar 

  • S. Juneja, and P. Shahabuddin, “Simulating heavy tailed processes using delayed hazard rate twisting,” ACM TOMACS vol. 12 pp. 94–118, 2002.

    Article  Google Scholar 

Download references

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Correspondence to Søren Asmussen.

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AMS 2000 Subject Classification

Primary 68M20, Secondary 60K25

†Partially supported by MaPhySto—A Network in Mathematical Physics and Stochastics, founded by the Danish National Research Foundation.

An erratum to this article is available at http://dx.doi.org/10.1007/s11009-006-7293-2.

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Asmussen, S., Pihlsgård, M. Performance Analysis with Truncated Heavy-Tailed Distributions. Methodol Comput Appl Probab 7, 439–457 (2005). https://doi.org/10.1007/s11009-005-5002-1

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  • DOI: https://doi.org/10.1007/s11009-005-5002-1

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