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Estimates for the Distributions of the Sums of Subexponential Random Variables

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Abstract

Let \(\left\{ {S_n } \right\}_{n \geqslant 1} \) be a random walk with independent identically distributed increments \(\left\{ {\xi _i } \right\}_{i \geqslant 1} \). We study the ratios of the probabilities P(S n >x) / P1 > x) for all n and x. For some subclasses of subexponential distributions we find upper estimates uniform in x for the ratios which improve the available estimates for the whole class of subexponential distributions. We give some conditions sufficient for the asymptotic equivalence P(S τ > x) ∼ E τ P1 > x) as x → ∞. Here τ is a positive integer-valued random variable independent of \(\left\{ {\xi _i } \right\}_{i \geqslant 1} \). The estimates obtained are also used to find the asymptotics of the tail distribution of the maximum of a random walk modulated by a regenerative process.

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References

  1. Athreya K.B. and Ney P. E., Branching Processes, Springer-Verlag, Berlin (1972).

    Google Scholar 

  2. Fuk D. H. and Nagaev S. V., “Probabilistic inequalities for sums of independent random variables,” Teor. Veroyatnost. i Primenen., 16, No. 4, 660–675 (1971).

    Google Scholar 

  3. Borovkov A. A., “Estimates for the distribution of sums and maxima of sums of random variables when the Cram´er condition is not satisfied,” Siberian Math. J., 41, No. 5, 811–848 (2000).

    Google Scholar 

  4. Embrechts P., Klüppelberg C., and Mikosch T., Modelling Extremal Events, Springer-Verlag, Berlin (1997).

    Google Scholar 

  5. Mikosch T. and Nagaev A., “Rates in approximations to ruin probabilities for heavy-tailed distributions,” Extremes, 4, No. 1, 67–78 (2001).

    Google Scholar 

  6. Greenwood P. and Monroe I., “Random stopping preserves regular variation of process distributions,” Ann. Probab., 5, 42–51 (1977).

    Google Scholar 

  7. Borovkov A. A. and Utev S. A., “Estimates for distributions of sums stopped at a Markov time,” Theory Probab. Appl., 38, No. 2, 259–272 (1993).

    Google Scholar 

  8. Borovkov A. A. and Borovkov K. A., “On large deviation probabilities for random walks. I. Regularly varying tails. II. Regularly exponential distribution tails,” Theory Probab. Appl., 16, 209–232 (2001).

    Google Scholar 

  9. Korshunov D. A., “Large deviation probabilities for the maxima of sums of independent summands with a negative mean and a subexponential distribution,” Theory Probab. Appl., 46, No. 2, 355–365 (2001).

    Google Scholar 

  10. Foss S. and Zachary S., “The maximum on a random time interval of a random walk with long-tailed increments and negative drift,” Ann. Appl. Probab., 13, 37–53 (2003).

    Google Scholar 

  11. Klüppelberg C., “Subexponential distributions and integrated tails,” J. Appl. Probab., 35, 325–347 (1988).

    Google Scholar 

  12. Chistyakov V. P., “A theorem on sums of independent positive random variables and its application to branching random processes,” Theory Probab. Appl., 9, No. 4, 640–648 (1964).

    Google Scholar 

  13. Cline D. B. H., “Convolution tails, product tails and domains of attraction,” Probab. Theory Related Fields, 72, 529–557 (1986).

    Google Scholar 

  14. Nagaev A. V., “A property of sums of independent random variables,” Teor. Veroyatnost. i Primenen., 22, No. 2, 335–346 (1977).

    Google Scholar 

  15. Foss S. and Zachary S., “Asymptotics for the maximum of a modulated random walk with heavy-tailed increments,” Analytic Methods in Applied Probability (in Memory of Fridrih Karpelevich), Amer. Math. Soc. Transl., 207, No. 2, 37–52 (2002).

    Google Scholar 

  16. Arndt K., “Asymptotic properties of the distribution of the supremum of a random walk on a Markov chain.,” Probab. Appl., 25, 309–324 (1980).

    Google Scholar 

  17. Alsmeyer G. and Sgibnev M., “On the tail behaviour of the supremum of a random walk defined on a Markov chain,” Yokohama Math. J., 46, 139–159 (1999).

    Google Scholar 

  18. Asmussen S., Schmidli H., and Schmidt V., “Tail probabilities for non-standard risk and queueing processes with subexponential jumps,” Adv. Appl. Probab., 31, No. 2, 422–447 (1999).

    Google Scholar 

  19. Takine T., “Subexponential asymptotics of the waiting time distribution in a single-server queue with multiple Markovian arrival streams,” Stochastic Models, 17, No. 4, 429–448 (2001).

    Google Scholar 

  20. Meyn S. P. and Tweedie R. L., Markov Chains and Stochastic Stability, Springer-Verlag, London (1993).

    Google Scholar 

  21. Embrechts P. and Goldie C. M., “On convolution tails,” Stochastic Process. Appl., 13, 263–278 (1982).

    Google Scholar 

  22. Borovkov A. A., Stochastic Processes in Queueing Theory, Springer-Verlag, New York; Berlin (1976).

    Google Scholar 

  23. Pakes A. G., “On the tail of waiting-time distribution,” J. Appl. Probab., 12, 555–564 (1975).

    Google Scholar 

  24. Veraverbeke N., “Asymptotic behaviour of Wiener–Hopf factors of a random walk,” Stochastic Process. Appl., 5, 27–37 (1977).

    Google Scholar 

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Shneer, V.V. Estimates for the Distributions of the Sums of Subexponential Random Variables. Siberian Mathematical Journal 45, 1143–1158 (2004). https://doi.org/10.1023/B:SIMJ.0000048931.70386.68

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  • DOI: https://doi.org/10.1023/B:SIMJ.0000048931.70386.68

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