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Decompounding poisson random sums: Recursively truncated estimates in the discrete case

Author

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  • Boris Buchmann
  • Rudolf Grübel

Abstract

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Suggested Citation

  • Boris Buchmann & Rudolf Grübel, 2004. "Decompounding poisson random sums: Recursively truncated estimates in the discrete case," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 56(4), pages 743-756, December.
    • Handle: RePEc:spr:aistmt:v:56:y:2004:i:4:p:743-756
    DOI: 10.1007/BF02506487
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    Citations

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    Cited by:

    1. Shota Gugushvili & Ester Mariucci & Frank van der Meulen, 2020. "Decompounding discrete distributions: A nonparametric Bayesian approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(2), pages 464-492, June.
    2. Gillen, David & Hasheminia, Hamed, 2013. "Estimating the demand responses for different sizes of air passenger groups," Transportation Research Part B: Methodological, Elsevier, vol. 49(C), pages 24-38.
    3. Martin Bøgsted & Susan Pitts, 2010. "Decompounding random sums: a nonparametric approach," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(5), pages 855-872, October.
    4. Shota Gugushvili & Frank Meulen & Peter Spreij, 2018. "A non-parametric Bayesian approach to decompounding from high frequency data," Statistical Inference for Stochastic Processes, Springer, vol. 21(1), pages 53-79, April.
    5. Gomes-Gonçalves, Erika & Gzyl, Henryk & Mayoral, Silvia, 2015. "Maxentropic approach to decompound aggregate risk losses," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 326-336.

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