Skip to main content
Log in

Anscombe’s Tests of Fit for the Negative Binomial Distribution

  • Published:
Journal of Statistical Theory and Practice Aims and scope Submit manuscript

Abstract

The negative binomial model is an important and flexible two parameter distribution that models data from many application areas. Here we re-examine tests of fit for the negative binomial distribution that were introduced by Anscombe (1950); they are based on a dispersion statistic U and a third moment statistic T. Small sample power calculations are given for U and T. We are not aware that such powers have been given previously. We show Anscombe’s tests are smooth tests in the sense of Rayner and Best (1989). Comparisons are made with an empirical probability generating function test suggested by Meintanis (2005). We suggest U not be used and that decisions on the fit of data to the negative binomial be made using bootstrap p-values rather than comparison with standard errors as suggested by Anscombe (1950). We show that tests based on a fourth moment component of a smooth test statistic have good power.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Anscombe, F.J., 1950. Sampling theory of the negative binomial and logarithmic distributions. Biometrika, 37, 358–382.

    Article  MathSciNet  Google Scholar 

  • Best, D.J., Rayner, J.C.W., 2003. Tests of fit for the geometric distribution. Communications in Statistics, Simulation and Computation, 32 (4), 1065–1078.

    Article  MathSciNet  Google Scholar 

  • Gürtler, N., Henze, N., 2000. Recent and classical goodness-of-fit tests for the Poisson distribution. Journal of Statistical Planning and Inference, 90, 207–225.

    Article  MathSciNet  Google Scholar 

  • Jarvis, B., 1989. Statistical Aspects of the Microbiological Analysis of Foods. Elsevier, Amsterdam.

    Google Scholar 

  • Johnson, N.L., Kemp, A.W., Kotz, S., 2005. Univariate Discrete Distributions (3rd edition). Wiley, New York.

    Book  Google Scholar 

  • Krebs, C.J., 1998. Ecological Methodology (2nd ed.). Addison-Wesley-Longman, New York.

    Google Scholar 

  • Lancaster, H.O., 1975. Joint probability in the Meixner classes. Journal of the Royal Statistical Society Series B, 37, 434–443.

    MathSciNet  MATH  Google Scholar 

  • Meintanis, S.G., 2005. Transform methods for testing for the negative binomial hypothesis. Statistica, LXV (3), 293-300.

    Google Scholar 

  • Rayner, J.C.W., Best, D.J., 1989. Smooth Tests of Goodness of Fit. Oxford University Press, New York.

    MATH  Google Scholar 

  • Rayner, J.C.W., Thas, O., Best, D.J., 2009. Smooth Tests of Goodness of Fit: Using R (2nd edition). Wiley, Singapore.

    Book  Google Scholar 

  • Stuart, A., Ord, K., 2005. Kendall’s Advanced Theory of Statistics. Vol. 1 (6th edition), Hodder Arnold, London.

  • Thas, O., Rayner, J.C.W., 2005. Smooth tests for the zero inflated Poisson distribution. Biometrics, 61 (3), 808–815.

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to D. J. Best.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Best, D.J., Rayner, J.C.W. & Thas, O. Anscombe’s Tests of Fit for the Negative Binomial Distribution. J Stat Theory Pract 3, 555–565 (2009). https://doi.org/10.1080/15598608.2009.10411946

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1080/15598608.2009.10411946

AMS Subject Classification

Key-words

Navigation