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On a generalization of the Rényi–Srivastava characterization of the Poisson law
Part of:
Distribution theory - Probability
Combinatorial probability
Combinatorics
Probability theory and stochastic processes
Mathematical modeling, applications of mathematics
Published online by Cambridge University Press: 25 February 2021
Abstract
We give a new method of proof for a result of D. Pierre-Loti-Viaud and P. Boulongne which can be seen as a generalization of a characterization of Poisson law due to Rényi and Srivastava. We also provide explicit formulas, in terms of Bell polynomials, for the moments of the compound distributions occurring in the extended collective model in non-life insurance.
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- © The Author(s), 2021. Published by Cambridge University Press on behalf of Applied Probability Trust
References
Feller, W. (1950). An Introduction to Probability Theory and its Applications, Vol. 2, 3rd edn. Wiley.Google Scholar
Kendall, M. G. and Stuart, A. (1994). The Advanced Theory of Statistics, Vol. 1, 6th edn.Google Scholar
Klugman, S. A., Panjer, H. H. and Willmot, G. E. (2012). Loss Models: From Data to Decisions, 4th edn. Wiley.Google Scholar
Johnson, N. L., Kemp, A. W. and Kotz, S. (2005). Univariate Discrete Distributions. Wiley-Interscience.CrossRefGoogle Scholar
Johnson, N. L., Kemp, A. W. and Kotz, S. (1997). Multivariate Discrete Distributions. Wiley-Interscience.Google Scholar
Partrat, C. and Besson, J.-L. (2005). Assurance non-vie: Modélisation, simulation. Economica.Google Scholar
Pierre Loti-Viaud, D. and Boulongne, P. (2014). Mathématiques et assurance: Premiers éléments. Ellipses.Google Scholar
Rényi, A. (1964). On two mathematical models of the traffic on a divided highway. J. Appl. Prob. 1, 311–320.CrossRefGoogle Scholar
Srivastava, R. C. (1971). On a characterization of the Poisson process. J. Appl. Prob. 8, 615–616.CrossRefGoogle Scholar
Sundt, B. and Vernic, R. (2009). Recursions for Convolutions and Compound Distributions with Insurance Applications. Springer Science & Business Media.Google Scholar