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Removing logarithms from Poisson process error bounds

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  • Brown, Timothy C.
  • Weinberg, Graham V.
  • Xia, Aihua

Abstract

We present a new approximation theorem for estimating the error in approximating the whole distribution of a finite-point process by a suitable Poisson process. The metric used for this purpose regards the distributions as close if there are couplings of the processes with the expected average distance between points small in the best-possible matching. In many cases, the new bounds remain constant as the mean of the process increases, in contrast to previous results which, at best, increase logarithmically with the mean. Applications are given to Bernoulli-type point processes and to networks of queues. In these applications the bounds are independent of time and space, only depending on parameters of the system under consideration. Such bounds may be important in analysing properties, such as queueing parameters which depend on the whole distribution and not just the distribution of the number of points in a particular set.

Suggested Citation

  • Brown, Timothy C. & Weinberg, Graham V. & Xia, Aihua, 2000. "Removing logarithms from Poisson process error bounds," Stochastic Processes and their Applications, Elsevier, vol. 87(1), pages 149-165, May.
    • Handle: RePEc:eee:spapps:v:87:y:2000:i:1:p:149-165
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    References listed on IDEAS

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    1. Barbour, A. D. & Brown, T. C., 1992. "Stein's method and point process approximation," Stochastic Processes and their Applications, Elsevier, vol. 43(1), pages 9-31, November.
    2. Brown, Timothy C. & Xia, Aihua, 1995. "On Stein-Chen factors for Poisson approximation," Statistics & Probability Letters, Elsevier, vol. 23(4), pages 327-332, June.
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    Cited by:

    1. Cong, Tianshu & Xia, Aihua & Zhang, Fuxi, 2020. "A large sample property in approximating the superposition of i.i.d. finite point processes," Stochastic Processes and their Applications, Elsevier, vol. 130(7), pages 4493-4511.
    2. Schuhmacher, Dominic, 2005. "Distance estimates for dependent superpositions of point processes," Stochastic Processes and their Applications, Elsevier, vol. 115(11), pages 1819-1837, November.
    3. Xia, Aihua & Zhang, Fuxi, 2008. "A polynomial birth-death point process approximation to the Bernoulli process," Stochastic Processes and their Applications, Elsevier, vol. 118(7), pages 1254-1263, July.

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