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Some goodness-of-fit tests for the Poisson distribution with applications in Biodosimetry

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  • Puig, Pedro
  • Weiß, Christian H.

Abstract

New characterizations of the Poisson distribution based on an identity involving the Binomial thinning operator are presented. These characterizations allow the construction of statistics for testing the Poisson distribution against alternatives belonging to a large family called the LC-class, and against general alternatives. The usefulness and the power of the tests are illustrated with several examples of applications in Biodosimetry.

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  • Puig, Pedro & Weiß, Christian H., 2020. "Some goodness-of-fit tests for the Poisson distribution with applications in Biodosimetry," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    • Handle: RePEc:eee:csdana:v:144:y:2020:i:c:s0167947319302336
    DOI: 10.1016/j.csda.2019.106878
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    References listed on IDEAS

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    1. Tammy Harris & Joseph M. Hilbe & James W. Hardin, 2014. "Modeling count data with generalized distributions," Stata Journal, StataCorp LP, vol. 14(3), pages 562-579, September.
    2. Hilbe,Joseph M., 2014. "Modeling Count Data," Cambridge Books, Cambridge University Press, number 9781107611252, September.
    3. Pedro Puig & Célestin C. Kokonendji, 2018. "Non†parametric Estimation of the Number of Zeros in Truncated Count Distributions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 45(2), pages 347-365, June.
    4. José González-Barrios & Federico O’Reilly & Raúl Rueda, 2006. "Goodness of Fit for Discrete Random Variables Using the Conditional Density," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 64(1), pages 77-94, August.
    5. Mònica Pujol & Joan-Francesc Barquinero & Pedro Puig & Roser Puig & María Rosa Caballín & Leonardo Barrios, 2014. "A New Model of Biodosimetry to Integrate Low and High Doses," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-19, December.
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    Cited by:

    1. Boris Aleksandrov & Christian H. Weiß & Simon Nik & Maxime Faymonville & Carsten Jentsch, 2024. "Modelling and diagnostic tests for Poisson and negative-binomial count time series," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 87(7), pages 843-887, October.
    2. Muhammad Aslam, 2022. "Neutrosophic F-Test for Two Counts of Data from the Poisson Distribution with Application in Climatology," Stats, MDPI, vol. 5(3), pages 1-11, August.

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