Skip to main content
Log in

Engen's extended negative binomial model revisited

  • Distribution
  • Published:
Annals of the Institute of Statistical Mathematics Aims and scope Submit manuscript

Abstract

The present article shows that a limiting argument that is essentially the law of small numbers produces a proper discrete multivariate distribution from any generalized Poisson distribution. Based on this result, Engen's Extended Negative Binomial (ENB) model is derived from the Poisson-Pascal distribution, which is a generalization of the inverse Gaussian-Poisson distribution. The ENB model is also derived from Sichel's generalized inverse Gaussian-Poisson distribution. The application of the ENB model is discussed thereto.

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 series distributions,Biometrika,37, 358–382.

    Article  MATH  MathSciNet  Google Scholar 

  • Breiman, L. (1968).Probability, Addison-Wesley, Reading, Massachusetts.

    MATH  Google Scholar 

  • Bunge, J. and Fitzpatrick, M. (1993). Estimating the number of species: A review,Journal of the American Statistical Association,88, 364–373.

    Article  Google Scholar 

  • Charalambides, C. A. and Singh, J. (1988). A review of the Stirling numbers, their generalizations and statistical applications,Communications in Statistics, Theory and Methods,17, 2533–2595.

    MATH  MathSciNet  Google Scholar 

  • Engen, S. (1974). On species frequency models,Biometrika,61, 263–270.

    Article  MATH  MathSciNet  Google Scholar 

  • Engen, S. (1977). Comments on two different approaches to the analysis of species frequency data,Biometrics,33, 205–213.

    Article  MATH  Google Scholar 

  • Engen, S. (1978).Stochastic Abundance Models, Chapman and Hall, London.

    MATH  Google Scholar 

  • Ewens, W. J. (1972). The sampling theory of selectively neutral alleles,Theoretical Population Biology,3, 87–112.

    Article  MATH  MathSciNet  Google Scholar 

  • Feller, W. (1957).An Introduction to Probability Theory and Its Applications, Vol. 1, 2nd ed., Wiley, New York.

    MATH  Google Scholar 

  • Fisher, R. A., Corbet, A. S. and Williams, C. B. (1943). The relation between the number of species and the number of individuals in a random sample of an animal population,Journal of Animal Ecology,12, 42–58.

    Article  Google Scholar 

  • Good, I. J. (1953). The population frequencies of species and the estimation of population parameters,Biometrika,40, 237–264.

    Article  MATH  MathSciNet  Google Scholar 

  • Gupta, R. C. (1974). Modified power series distributions and some of its applications,Sankhyā B,36, 288–298.

    MATH  Google Scholar 

  • Hoshino, N. (2001). Applying Pitman's sampling formula to microdata disclosure risk assessment,Journal of Official Statistics,17, 499–520.

    Google Scholar 

  • Hoshino, N. (2002). On limiting random partition structure derived from the conditional inverse Gaussian-Poisson distribution, Technical Report, CMU-CALD-02-100, School of Computer Science, Carnegie Mellon University.

  • Hoshino, N. (2003). Random clustering based on the conditional inverse Gaussian-Poisson distribution,Journal of the Japan Statistical Society,33, 105–117.

    MATH  MathSciNet  Google Scholar 

  • Hoshino, N. and Takemura, A. (1998). Relationship between logarithmic series model and other superpopulation models useful for microdata disclosure risk assessment,Journal of the Japan Statistical Society,28(2), 125–134.

    MATH  MathSciNet  Google Scholar 

  • Johnson, N. L., Kotz, S. and Kemp, A. W. (1993).Univariate Discrete Distributions, 2nd ed., Wiley, New York.

    MATH  Google Scholar 

  • Johnson, N. L., Kotz, S. and Balakrishnan, N. (1997).Discrete Multivariate Distributions, Wiley, New York.

    MATH  Google Scholar 

  • Jørgensen, B. (1982).Statistical Properties of the Generalized Inverse Gaussian Distribution, Lecture Notes in Statistics, No. 9, Springer, New York.

    MATH  Google Scholar 

  • Kemp, A. W. (1978). Cluster size probabilities for generalized Poisson distributions,Communications in Statistics, Theory and Methods,7, 1433–1438.

    MathSciNet  Google Scholar 

  • Khatri, C. G. and Patel, I. R. (1961). Three classes of univariate discrete distributions,Biometrics,17, 567–575.

    Article  MATH  Google Scholar 

  • Mandelbrot, B. B. (1983).The Fractal Geometry of Nature, W. H. Freeman and Company, New York.

    MATH  Google Scholar 

  • Mehninick, E. F. (1964). A comparison of some species individuals diversity indices applied to samples of field insects.Ecology,45, 859–861.

    Article  Google Scholar 

  • Mosimann, J. E. (1962). On the compound multinomial distribution, the multivariate β-distribution and correlations among proportions,Biometrika,49, 65–82.

    Article  MATH  MathSciNet  Google Scholar 

  • Noack, A. (1950). A class of random variables with discrete distributions,Annals of Mathematical Statistics,21, 127–132.

    MATH  MathSciNet  Google Scholar 

  • Pitman, J. (1995). Exchangeable and partially exchangeable random partitions,Probability Theory and Related Fields,102, 145–158.

    Article  MATH  MathSciNet  Google Scholar 

  • Seshadri, V. (1999).The Inverse Gaussian Distribution, Springer, New York.

    MATH  Google Scholar 

  • Sibuya, M. (1979). Generalized hypergeometric, digamma and trigamma distribution,Annals of the Institute of Statistical Mathematics,31, 373–390.

    Article  MATH  MathSciNet  Google Scholar 

  • Sibuya, M. (1993). A random clustering process,Annals of the Institute of Statistical Mathematics,45, 459–465.

    Article  MATH  MathSciNet  Google Scholar 

  • Sibuya, M., Yoshimura, M. and Shimizu, R. (1964). Negative multinomial distribution,Annals of the Institute of Statistical Mathematics,16, 409–426.

    Article  MATH  MathSciNet  Google Scholar 

  • Sichel, H. S. (1971). On a family of discrete distributions particularly suited to represent long-tailed frequency data,Proceedings of the Third Symposium on Mathematical Statistics (ed. N. F. Laubscher),S.A. C.S.I.R., Pretoria, 51–97.

  • Sichel, H. S. (1974). On a distribution representing sentence-length in written prose,Journal of the Royal Statistical Society, Ser. A,137, 25–34.

    Google Scholar 

  • Sichel, H. S. (1992). Anatomy of the generalized inverse Gaussian-Poisson distribution with special applications to bibliometric studies,Information Processing and Management,28, 5–17.

    Article  Google Scholar 

  • Sichel, H. S. (1997). Modelling species-abundance frequencies and species-individual functions with the generalized inverse Gaussian-Poisson distribution,South African Statistical Journal,31, 13–37.

    MATH  Google Scholar 

  • Steutel, F. W. and van Harn, K. (1979). Discrete analogues of self-decomposability and stability,Annals of Probability,7, 893–899.

    MATH  MathSciNet  Google Scholar 

  • Watterson, G. A. (1974). Models for the logarithmic species abundance distributions,Theoretical Population Biology,6, 217–250.

    Article  MathSciNet  Google Scholar 

  • Willmot, G. E. (1986). Mixed compound Poisson distributions,ASTIN Bulletin,16, S59-S79.

    Article  Google Scholar 

  • Willmot, G. E. (1989). A remark on the Poisson-Pascal and some other contagious distributions,Statistics and Probability Letters,7, 217–220.

    Article  MathSciNet  Google Scholar 

  • Yamato, H., Sibuya, M. and Nomachi, T. (2001). Ordered sample from two-parameter GEM distribution,Statistics and Probability Letters,55, 19–27.

    Article  MATH  MathSciNet  Google Scholar 

  • Zipf, G. K. (1949).Human Behavior and the Principle of Least Effort, Addison-Wesley, Cambridge, Massachusetts.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

About this article

Cite this article

Hoshino, N. Engen's extended negative binomial model revisited. Ann Inst Stat Math 57, 369–387 (2005). https://doi.org/10.1007/BF02507030

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02507030

Key words and phrases

Navigation