Skip to main content
Log in

A Charlier–Parseval approach to poisson approximation and its applications

  • Published:
Lithuanian Mathematical Journal Aims and scope Submit manuscript

Abstract

We propose a new approach to Poisson approximation. The basic idea is very simple and based on properties of the Charlier polynomials and the Parseval identity. Such an approach quickly leads to new effective bounds for several Poisson approximation problems. We also give a selected survey on diverse Poisson approximation results.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. D. Aldous, Probability Approximations via the Poisson Clumping Heuristic, Springer-Verlag, New York, 1989.

    MATH  Google Scholar 

  2. T.V. Arak and A.Yu. Zaĭtsev, Uniform Limit Theorems for Sums of Independent Random Variables, English transl.: Proc. Steklov Inst. Math. 1988, no 1, Amer. Math. Soc., Providence, RI, 1988.

  3. A.D. Barbour, Asymptotic expansions in the Poisson limit theorem, Ann. Probab., 15:748–766, 1987.

    Article  MATH  MathSciNet  Google Scholar 

  4. A.D. Barbour, Topics in Poisson approximation, in D.N. Shanbhag and C.R. Rao (Eds.), Stochastic Processes: Theory and Methods, Handbook of Statistics, Vol. 19, North-Holland, Amsterdam, 2001, pp. 79–115.

    Google Scholar 

  5. A.D. Barbour, V. Čekanavičius, and A. Xia, On Stein’s method and perturbations, ALEA Lat. Am. J. Probab. Math. Stat., 3:31–53, 2007.

    MATH  MathSciNet  Google Scholar 

  6. A.D. Barbour and L.H.-Y. Chen, Stein’s Method and Applications, Singapore Univ. Press,World Scientific Publishing Co., Singapore, 2005.

    Book  Google Scholar 

  7. A.D. Barbour and O. Chryssaphinou, Compound Poisson approximation: A user’s guide, Ann. Appl. Probab., 11:964–1002, 2001.

    Article  MATH  MathSciNet  Google Scholar 

  8. A.D. Barbour and P. Hall, On the rate of Poisson convergence, Math. Proc. Cambridge Philos. Soc., 95:473–480, 1984.

    Article  MATH  MathSciNet  Google Scholar 

  9. A.D. Barbour, L. Holst, and S. Janson, Poisson Approximation, Oxford Science Publications, Clarendon Press, Oxford, 1992.

    MATH  Google Scholar 

  10. A.D. Barbour and J.L. Jensen, Local and tail approximations near the Poisson limit, Scand. J. Stat., 16:75–87, 1989.

    MATH  MathSciNet  Google Scholar 

  11. A.D. Barbour and A. Xia, Poisson perturbations, ESAIM Probab. Stat., 3:131–150, 1999.

    Article  MATH  MathSciNet  Google Scholar 

  12. A.D. Barbour and A. Xia, On Stein’s factors for Poisson approximation in Wasserstein distance, Bernoulli, 12:943–954, 2006.

    Article  MATH  MathSciNet  Google Scholar 

  13. R.P. Boas Jr., Representation of probability distributions by Charlier series, Ann. Math. Stat., 20:376–392, 1949.

    Article  MATH  MathSciNet  Google Scholar 

  14. I.S. Borisov and I.S. Vorozheĭkin, Accuracy of approximation in the Poisson theorem in terms of the χ2-distance, Sib. Math. J., 49:5–17, 2008.

    Article  MathSciNet  Google Scholar 

  15. K.A. Borovkov, On the problem of improving Poisson approximation, Theory Probab. Appl., 33:343–347, 1989.

    Article  MathSciNet  Google Scholar 

  16. K.A. Borovkov and D. Pfeifer, On improvements of the order of approximation in the Poisson limit theorem, J. Appl. Probab., 33:146–155, 1996.

    Article  MATH  MathSciNet  Google Scholar 

  17. L. von Bortkiewicz, Das Gesetz der Kleinen Zahlen, B.G. Teubner, Leipzig, 1898.

    Google Scholar 

  18. V. Čekanavičius, Asymptotic expansions in the exponent: A compound Poisson approach, Adv. Appl. Probab., 29:374–387, 1997.

    Article  MATH  Google Scholar 

  19. V. Čekanavičius, On local estimates and the Stein method, Bernoulli, 10:665–683, 2004.

    Article  MATH  MathSciNet  Google Scholar 

  20. V. Čekanavičius and J. Kruopis, Signed Poisson approximation: A possible alternative to normal and Poisson laws, Bernoulli, 6:591–606, 2000.

    Article  MATH  MathSciNet  Google Scholar 

  21. C.V.L. Charlier, Die zweite Form des Fehlergesetzes, Ark. Mat. Astron. Fys., 2(15):1–8, 1905.

    Google Scholar 

  22. S. Chatterjee, P. Diaconis, and E. Meckes, Exchangeable pairs and Poisson approximation, Probab. Surv., 2:64–106, 2005.

    Article  MathSciNet  Google Scholar 

  23. L.H.Y. Chen, Poisson approximation for dependent trials, Ann. Probab., 3:534–545, 1975.

    Article  MATH  Google Scholar 

  24. L. Comtet, Advanced Combinatorics, revised and enlarged edition, D. Reidel Publishing Co., Dordrecht, 1974.

    Google Scholar 

  25. D.J. Daley, A note on bounds for the supremum metric for discrete random variables, Math. Nachr., 99:95–98, 1980.

    Article  MATH  MathSciNet  Google Scholar 

  26. D.J. Daley and D. Vere-Jones, An Introduction to the Theory of Point Processes. Vol. II. General Theory and Structure, 2nd edition, Springer, New York, 2008.

    Google Scholar 

  27. A. de Moivre, The Doctrine of Chances, 3rd edition, W. Pearson, London, 1756; available at www.ibiblio.org/chance.

  28. P. Deheuvels, A. Karr, D. Pfeifer, and R. R. Serfling, Poisson approximations in selected metrics by coupling and semigroup methods with applications, J. Stat. Plann. Inference, 20:1–22, 1988.

    Article  MATH  MathSciNet  Google Scholar 

  29. P. Deheuvels and D. Pfeifer, Operator semigroups and Poisson convergence in selected metrics, Semigroup Forum, 34:203–224, 1986. Errata: Semigroup Forum, 35:251.

    Google Scholar 

  30. P. Deheuvels and D. Pfeifer, A semigroup approach to Poisson approximation, Ann. Probab., 14:663–676, 1986.

    Article  MATH  MathSciNet  Google Scholar 

  31. P. Deheuvels and D. Pfeifer, On a relationship between Uspensky’s theorem and Poisson approximation, Ann. Inst. Stat. Math., 40:671–681, 1988.

    Article  MATH  MathSciNet  Google Scholar 

  32. P. Deheuvels, D. Pfeifer, and M.L. Puri, A new semigroup technique in Poisson approximation, Semigroup Forum, 38:189–201, 1989.

    Article  MATH  MathSciNet  Google Scholar 

  33. W. Ehm, Binomial approximation to the Poisson binomial distribution, Stat. Probab. Lett., 11:7–16, 1991.

    Article  MATH  MathSciNet  Google Scholar 

  34. A.A. Fedotov, P. Harremoës, and F. Topsøe, Refinements of Pinsker’s inequality, IEEE Trans. Inform. Theory, 49:1491–1498, 2003.

    Article  MATH  MathSciNet  Google Scholar 

  35. P. Franken, Approximation des Verteilungen von Summen unabhangiger nichtnegativer ganzzahler Zufallsgrossen durch Poissonsche verteilungen, Math. Nachr., 23:303–340, 1964.

    Article  MathSciNet  Google Scholar 

  36. L. Goldstein and G. Reinert, Distributional transformations, orthogonal polynomials, and Stein characterizations, J. Theor. Probab., 18:237–260, 2005.

    Article  MATH  MathSciNet  Google Scholar 

  37. I.J. Good, Some statistical applications of Poisson’s work (with comments by Persi Diaconis and Eduardo Engel, Herbert Solomon, C.C. Heyde, and Nozer D. Singpurwalla, and with a reply by the author), Stat. Sci., 1:157–180, 1986.

    Article  MathSciNet  Google Scholar 

  38. F.A. Haight, Handbook of the Poisson Distribution, John Wiley & Sons, Inc., New York, London, Sydney.

  39. H. Herrmann, Variationsabstand zwischen der Verteilung einer Summe unabhängiger nichtnegativer ganzzahliger Zufallsgrössen und Poissonschen Verteilungen, Math. Nachr., 29:265–289, 1965.

    Article  MATH  MathSciNet  Google Scholar 

  40. C. Hipp, Approximation of aggregate claims distributions by compound Poisson distributions, Insur. Math. Econ., 4:227–232, 1985. Correction note: Insur. Math. Econ., 6:165, 1987.

    Google Scholar 

  41. C. Hipp, Improved approximations for the aggregate claims distribution in the individual model, Astin Bull., 16:89–100, 1986.

    Article  Google Scholar 

  42. J.L. Hodges Jr. and L. Le Cam, The Poisson approximation to the Poisson binomial distribution, Ann. Math. Stat., 31:737–740, 1960.

    Article  MATH  Google Scholar 

  43. H.-K. Hwang, Asymptotics of Poisson approximation to random discrete distributions: an analytic approach, Adv. Appl. Probab., 31:448–491, 1999.

    Article  MATH  Google Scholar 

  44. H.-K. Hwang and V. Zacharovas, Uniform asymptotics of Poisson approximation to the Poisson-binomial distribution, Theory Probab. Appl., 2010 (in press).

  45. M. Jacob, Sullo sviluppo di una curva di frequenze in serie di Charlier tipo B, G. Ist. Ital. Attuari, 4:221–234, 1933.

    Google Scholar 

  46. S. Janson, Coupling and Poisson approximation, Acta Appl. Math., 34:7–15, 1994.

    Article  MATH  MathSciNet  Google Scholar 

  47. C. Jordan, Sur la probabilité des épreuves répétées, le théorème de Bernoulli et son inversion, Bull. Soc. Math. Fr., 54:101–137, 1926.

    Google Scholar 

  48. J.E. Kennedy and M.P. Quine, The total variation distance between the binomial and Poisson distributions, Ann. Probab., 17:396–400, 1989.

    Article  MATH  MathSciNet  Google Scholar 

  49. J. Kerstan, Verallgemeinerung eines Satzes von Prochorow und Le Cam, Z. Wahrscheinlichkeitstheor. Verw. Geb., 2:173–179, 1964.

    Article  MATH  MathSciNet  Google Scholar 

  50. A.N. Kolmogorov, Two uniform limit theorems for sums of independent random variables, Theory Probab. Appl., 1:384–394, 1956.

    Article  Google Scholar 

  51. I. Kontoyiannis, P. Harremöes, and O. Johnson, Entropy and the law of small numbers, IEEE Trans. Inform. Theory, 51:466–472, 2005.

    Article  MathSciNet  Google Scholar 

  52. P.S. Kornya, Distribution of aggregate claims in the individual risk theory model, Trans. Soc. Actuaries, 35:823–858, 1983.

    Google Scholar 

  53. Y. Kruopis, The accuracy of approximation of the generalized binomial distribution by convolutions of Poisson measures, Lith. Math. J., 26:37–49, 1986.

    Article  MATH  Google Scholar 

  54. L. Le Cam, An approximation theorem for the Poisson binomial distribution, Pac. J. Math., 10:1181–1197, 1960.

    MATH  Google Scholar 

  55. H. Makabe, On the approximations to some limiting distributions with some applications, Kōdai Math. Semin. Rep., 14:123–133, 1962.

    Article  MATH  MathSciNet  Google Scholar 

  56. T. Matsunawa, Uniform φ-equivalence of probability distributions based on information and related measures of discrepancy, Ann. Inst. Stat. Math., 34:1–17, 1982.

    Article  MATH  MathSciNet  Google Scholar 

  57. K. Neammanee, A nonuniform bound for the approximation of Poisson binomial by Poisson distribution, Int. J. Math. Math. Sci., 48:3041–3046, 2003.

    Article  MathSciNet  Google Scholar 

  58. K. Neammanee, Pointwise approximation of Poisson distribution, Stoch. Model. Appl., 6:20–26, 2003.

    Google Scholar 

  59. D. Pfeifer, A semigroup setting for distance measures in connexion with Poisson approximation, Semigroup Forum, 31:201–205, 1985.

    Article  MATH  MathSciNet  Google Scholar 

  60. J. Pitman, Probabilistic bounds on the coefficients of polynomials with only real zeros, J. Comb. Theory Ser. A, 77:279–303, 1997.

    Article  MATH  MathSciNet  Google Scholar 

  61. S.D. Poisson, Recherches sur la probabilité des jugements en matière criminelle et en matière civile: Précedés des règles générales du calcul des probabilités, Bachelier, Paris, 1837.

    Google Scholar 

  62. H. Pollaczek-Geiringer, Die Charlier’sche Entwicklung willkürlicher Verteilungen, Skand. Aktuarietidskr., 11:98–111, 1928.

    MATH  Google Scholar 

  63. H.V. Poor, The maximum difference between the binomial and Poisson distributions, Stat. Probab. Lett., 11:103–106, 1991.

    Article  MATH  MathSciNet  Google Scholar 

  64. È.L. Presman, Approximation of binomial distributions by infinitely divisible ones, Theory Probab. Appl., 28:393–403, 1983.

    Article  MathSciNet  Google Scholar 

  65. È.L. Presman, The variation distance between the distribution of a sum of independent Bernoulli variables and the Poisson law, Teor. Veroyatn. Primen., 30(2):391–396, 1985 (in Russian).

    MATH  MathSciNet  Google Scholar 

  66. Y.V. Prokhorov, Asymptotic behavior of the binomial distribution, Usp. Mat. Nauk, 8:135–142, 1953. Also in Sel. Transl. Math. Stat. Probab., 1:87–95.

  67. A. Röllin, Translated Poisson approximation using exchangeable pair couplings, Ann. Appl. Probab., 17:1596–1614, 2007.

    Article  MATH  MathSciNet  Google Scholar 

  68. M. Romanowska, A note on the upper bound for the distance in total variation between the binomial and the Poisson distribution, Stat. Neerl., 31:127–130, 1977.

    Article  MATH  MathSciNet  Google Scholar 

  69. B. Roos, A semigroup approach to Poisson approximation with respect to the point metric, Stat. Probab. Lett., 24:305–314, 1995.

    Article  MATH  MathSciNet  Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

  71. B. Roos, Sharp constants in the Poisson approximation, Stat. Probab. Lett., 52:155–168, 2001.

    Article  MATH  MathSciNet  Google Scholar 

  72. B. Roos, Poisson approximation via the convolution with Kornya–Presman signed measures, Theory Probab. Appl., 48:555–560, 2004.

    Article  MathSciNet  Google Scholar 

  73. B. Roos, On variational bounds in the compound Poisson approximation of the individual risk model, Insur. Math. Econ., 40:403–414, 2007.

    Article  MATH  MathSciNet  Google Scholar 

  74. E. Schmidt, Uber die Charlier–Jordansche Entwicklung einer willkurlichen Funktion nach der Poissonschen Funktion und ihren Ableitungen, Z. Angew. Math., 13:139–142, 1933.

    Google Scholar 

  75. E. Seneta, Modern probabilistic concepts in the work of E. Abbe and A. de Moivre, Math. Sci., 8:75–80, 1983.

    MATH  MathSciNet  Google Scholar 

  76. R.J. Serfling, Probability inequalities for the sum in sampling without replacement, Ann. Stat., 2:39–48, 1974.

    Article  MATH  MathSciNet  Google Scholar 

  77. R.J. Serfling, Some elementary results on Poisson approximation in a sequence of Bernoulli trials, SIAM Rev., 20:567–579, 1978.

    Article  MATH  MathSciNet  Google Scholar 

  78. S.Y. Shorgin, Approximation of a generalized binomial distribution, Theory Probab. Appl., 22:846–850, 1977.

    Article  MATH  Google Scholar 

  79. R. Siegmund-Schultze, Hilda Geiringer-von Mises, Charlier series, ideology, and the human side of the emancipation of applied mathematics at the University of Berlin during the 1920s, Hist. Math., 20:364–381, 1993.

    Article  MATH  MathSciNet  Google Scholar 

  80. J.M. Steele, Le Cam’s inequality and Poisson approximations, Am. Math. Mon., 101:48–54, 1994.

    Article  MATH  MathSciNet  Google Scholar 

  81. C. Stein, Approximate Computation of Expectations, IMS, Hayward, CA, 1986.

    MATH  Google Scholar 

  82. G. Szegö, Orthogonal Polynomials, Amer. Math. Soc., New York, 1939.

    Google Scholar 

  83. K. Teerapabolarn and K. Neammanee, Poisson approximation for sums of dependent Bernoulli random variables, Acta Math. Acad. Paedagog. Nyházi. (N.S.), 22:87–99, 2006.

    MATH  MathSciNet  Google Scholar 

  84. J.V. Uspensky, On Ch. Jordan’s series for probability, Ann. Math., 32:306–312, 1931.

    Article  MathSciNet  Google Scholar 

  85. W. Vervaat, Upper bounds for the distance in total variation between the binomial or negative binomial and the Poisson distribution, Stat. Neerl., 23:79–86, 1969.

    Article  MATH  MathSciNet  Google Scholar 

  86. M. Weba, Bounds for the total variation distance between the binomial and the Poisson distribution in the case of medium-sized success probabilities, J. Appl. Probab., 36:97–104, 1999.

    Article  MATH  MathSciNet  Google Scholar 

  87. H.-J. Witte, A unification of some approaches to Poisson approximation, J. Appl. Probab., 27:611–621, 1990.

    Article  MATH  MathSciNet  Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to H.-K. Hwang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zacharovas, V., Hwang, HK. A Charlier–Parseval approach to poisson approximation and its applications. Lith Math J 50, 88–119 (2010). https://doi.org/10.1007/s10986-010-9073-5

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10986-010-9073-5

MSC

Keywords

Navigation