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Poisson approximation of multivariate Poisson mixtures

Published online by Cambridge University Press:  14 July 2016

Bero Roos*
Affiliation:
Universität Hamburg
*
Postal address: Fachbereich Mathematik, SPST, Universität Hamburg, Bundesstraße 55, 20146 Hamburg, Germany. Email address: roos@math.uni-hamburg.de

Abstract

We show how good multivariate Poisson mixtures can be approximated by multivariate Poisson distributions and related finite signed measures. Upper bounds for the total variation distance with applications to risk theory and generalized negative multinomial distributions are given. Furthermore, it turns out that the ideas used in this paper also lead to improvements in the Poisson approximation of generalized multinomial distributions.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 2003 

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References

Aitchison, J., and Ho, C. H. (1989). The multivariate Poisson-log normal distribution. Biometrika 76, 643653.Google Scholar
Barbour, A. D. (1988). Stein's method and Poisson process convergence. In A Celebration of Applied Probability (J. Appl. Prob. Spec. Vol. 25A), ed. Gani, J., Applied Probability Trust, Sheffield, pp. 175184.Google Scholar
Barbour, A. D., Holst, L., and Janson, S. (1992). Poisson Approximation. Oxford University Press.Google Scholar
Barndorff-Nielsen, O. E., Blasild, P., and Seshadri, V. (1992). Multivariate distributions with generalized inverse Gaussian marginals, and associated Poisson mixtures. Canad. J. Statist. 20, 109120.Google Scholar
Chihara, T. S. (1978). An Introduction to Orthogonal Polynomials (Math. Appl. 13). Gordon and Breach Science Publishers, New York.Google Scholar
Dey, D. K., and Chung, Y. (1992). Compound Poisson distributions: properties and estimation. Commun. Statist. Theory Meth. 21, 30973121.Google Scholar
Douglas, J. B. (1980). Analysis with Standard Contagious Distributions. International Co-operative Publishing House, Fairland, MD.Google Scholar
Falk, M., and Reiss, R.-D. (1992). Poisson approximation of empirical processes. Statist. Prob. Lett. 14, 3948.Google Scholar
Grandell, J. (1997). Mixed Poisson Processes. Chapman and Hall, London.CrossRefGoogle Scholar
Haight, F. A. (1967). Handbook of the Poisson Distribution. John Wiley, New York.Google Scholar
Johnson, N. L., Kotz, S., and Balakrishnan, N. (1997). Discrete Multivariate Distributions. John Wiley, New York.Google Scholar
Johnson, N. L., Kotz, S., and Kemp, A. W. (1993). Univariate Discrete Distributions, 2nd edn. John Wiley, New York.Google Scholar
Kopociński, B. (1999). Multivariate negative binomial distributions generated by multivariate exponential distributions. Appl. Math. 25, 463472.Google Scholar
Partrat, C. (1994). Compound model for two dependent kinds of claim. Insurance Math. Econom. 15, 219231.Google Scholar
Pfeifer, D. (1987). On the distance between mixed Poisson and Poisson distributions. Statist. Decisions 5, 367379.Google Scholar
Reiss, R.-D. (1989). Approximate Distributions of Order Statistics. Springer, New York.Google Scholar
Roos, B. (1998). Metric multivariate Poisson approximation of the generalized multinomial distribution. Theory Prob. Appl. 43, 306315.Google Scholar
Roos, B. (1999a). Asymptotics and sharp bounds in the Poisson approximation to the Poisson-binomial distribution. Bernoulli 5, 10211034.Google Scholar
Roos, B. (1999b). On the rate of multivariate Poisson convergence. J. Multivariate Anal. 69, 120134.Google Scholar
Roos, B. (2002). Kerstan's method for compound Poisson approximation. To appear in Ann. Prob.Google Scholar
Roos, B. (2003). Improvements in the Poisson approximation of mixed Poisson distributions. J. Statist. Planning Infer. 113, 467483.Google Scholar
Wang, Y. H. (1986). Coupling methods in approximations. Canad. J. Statist. 14, 6974.Google Scholar
Yannaros, N. (1991). Poisson approximation for random sums of Bernoulli random variables. Statist. Prob. Lett. 11, 161165.Google Scholar