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Goodness of fit for the Poisson distribution

Author

Listed:
  • Best, D. J.
  • Rayner, J. C. W.

Abstract

Two problems with the usual X2 test of fit for the Poisson distribution are how to pool the data and how much power is lost by this pooling. Smooth tests of fit as outlined in Rayner and Best (1989) avoid the pooling problems and provide weakly optimal and therefore powerful tests. Power comparisons between X2, smooth tests and a modified Kolmogorov-Smirnov statistic are given.

Suggested Citation

  • Best, D. J. & Rayner, J. C. W., 1999. "Goodness of fit for the Poisson distribution," Statistics & Probability Letters, Elsevier, vol. 44(3), pages 259-265, September.
  • Handle: RePEc:eee:stapro:v:44:y:1999:i:3:p:259-265
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    Cited by:

    1. Székely, Gábor J. & Rizzo, Maria L., 2004. "Mean distance test of Poisson distribution," Statistics & Probability Letters, Elsevier, vol. 67(3), pages 241-247, April.
    2. Subhadeep Mukhopadhyay, 2021. "Density Sharpening: Principles and Applications to Discrete Data Analysis," Papers 2108.07372, arXiv.org, revised Aug 2021.
    3. J. I. Beltrán-Beltrán & F. J. O’Reilly, 2019. "On goodness of fit tests for the Poisson, negative binomial and binomial distributions," Statistical Papers, Springer, vol. 60(1), pages 1-18, February.

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