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Centered Poisson Approximation via Stein's Method

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Abstract

The centered Poisson approximation can be considered as a link between the Poisson and normal laws. It has the structure similar to the Poisson distribution but depends on two parameters. The results obtained via the Stein–Chen method for sums of independent and dependent indicators show that the centred Poisson approximation is a strong alternative to the standard Poisson and normal approximations and, potentially, is more widely applicable.

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References

  1. M. Abramowitz, A. Stegun, Handbook of Mathematical Functions, Dover, New York (1964).

  2. D. J. Aldous, Probability Approximations via the Poisson Clumping Heuristic, Springer, New York (1989).

    Google Scholar 

  3. A. Aleškevičienė and V. Statulevičius, Asymptotic expansions in the approximation by the Poisson law, Lith. Math. J., 35(4), 309–327 (1995).

    Google Scholar 

  4. R. Arratia, L. Goldstein, L. Gordon, Poisson approximation and the Stein–Chen method, Statist. Sci., 5, 403–434 (1990).

    Google Scholar 

  5. A. D. Barbour, L. H. Y. Chen, K. P. Choi, Poisson approximation for unbounded functions, I: independent summands, Statist. Sinica, 5, 749–766 (1995).

    Google Scholar 

  6. A. D. Barbour, P. Hall, On the rate of Poisson convergence, Math. Proc. Cambridge Philos. Soc., 95, 473–480 (1984).

    Google Scholar 

  7. A. D. Barbour, L. Holst, S. Janson, Poisson Approximations, Oxford University Press, Oxford (1992).

    Google Scholar 

  8. A. D. Barbour, J. L. Jensen, Local and tail approximation near the Poisson limit, Scand. J. Statist., 16, 75–87 (1989).

    Google Scholar 

  9. A. D. Barbour, A. Xia, Poisson perturbations, ESAIM: Probability and Statistics, 3, (1999).

  10. V. Čekanavičius, On signed normal – Poisson approximations, Probab. Theory Related Fields, 111, 565–583 (1998).

    Google Scholar 

  11. V. Čekanavičius, Poisson approximations for sequences of random variables, Statist. Probab. Letters, 39, 101–107 (1998).

    Google Scholar 

  12. L. H. Y. Chen, K. P. Choi, Some asymptotic and large deviations results in Poisson approximations, Ann. Probab., 20, 1867–1876 (1992).

    Google Scholar 

  13. L. H. Y. Chen, Poisson approximation for dependent trials, Ann. Probab., 3, 534–545 (1975).

    Google Scholar 

  14. P. Deheuvels, D. Pfeifer, A semigroup approach to Poisson approximation, Ann. Probab., 14, 663–676 (1986).

    Google Scholar 

  15. W. Ehm, Binomial approximation to the Poisson binomial distribution, Statist. Probab. Letters, 11, 7–16 (1991).

    Google Scholar 

  16. J. Kerstan, Verallgemeinerung eines Satzes von Prochorow und Le Cam, Z. Wahrsch. verw. Gebiete, 2, 173–179 (1964).

    Google Scholar 

  17. J. Kruopis, Precision of approximations of the generalized binomial distribution by convolutions of Poisson measures, Lith. Math. J., 26(1), 37–49 (1986).

    Google Scholar 

  18. L. Le Cam, An approximation theorem for the Poisson binomial distribution, Pacific J. Math., 10, 1181–1197 (1960).

    Google Scholar 

  19. L. Le Cam, On the distribution of sums of independent random variables, in: Bernoulli, Bayes, Laplace (Anniversary volume), Springer, New York (1965), pp. 179–202.

    Google Scholar 

  20. Yu. V. Prokhorov, Asymptotic behavior of the binomial distribution, Usp. Mat. Nauk, 8(3), 135–142 (1953).

    Google Scholar 

  21. B. Roos, Asymptotics and sharp bounds in the Poisson approximation to the Poisson-binomial distribution, Bernoulli, 5, 1021–1034 (1999).

    Google Scholar 

  22. S. Y. T. Soon, Binomial approximation for dependent indicators, Statist. Sinica, 6, 703–714 (1996).

    Google Scholar 

  23. C. Stein, A bound for the error in the normal approximation to the distribution of a sum of dependent random variables, Proc. 6th Berkeley Symp. Math. Statist. Probab., 2, 583–602 (1970).

    Google Scholar 

  24. A. Xia, On using the first difference in the Stein–Chen method, Ann. Appl. Probab., 7(4), 899–916 (1997).

    Google Scholar 

  25. Y. H. Wang, On the number of successes in independent trials, Statist. Sinica, 3, 295–312 (1993).

    Google Scholar 

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Čekanavičius, V., Vaitkus, P. Centered Poisson Approximation via Stein's Method. Lithuanian Mathematical Journal 41, 319–329 (2001). https://doi.org/10.1023/A:1013804403291

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