Abstract
The main goal of this paper is to introduce new exponential families, that come from the concept of weighted distribution, that include and generalize the Poisson distribution. In these families there are distributions with index of dispersion greater than, equal to or smaller than one. This property makes them suitable to fit discrete data in overdispersion or underdispersion situations. We study the statistical properties of the families and we provide a useful interpretation of the parameters. Two classical examples are considered in order to compare the fits with some other distributions. To obtain the fits with the new family, the study of the profile log-likelihood is required.
Similar content being viewed by others
REFERENCES
Barndorff-Nielsen, O. (1978). Information and Exponential Families in Statistical Theory, Wiley, Norwich.
Brown, L. D. (1986). Fundamentals of Btatistical Exponential Funvilies, Lecture Notes-Monograph Series, Institute of Mathematical Statistics, California.
Castillo, J. (1994). The singly truncated Normal distribution a non-steep exponential family, Ann. Inst. Statist. Math., 46(1), 57–66.
Consul, P. C. (1989). Generalized Poisson Distributions, Marcel Dekker, New York.
Efron, B. (1978). The geometry of exponential families, Ann. Statist., 6, 362–376.
Greenwood, M. and Yule, U. (1920). An inquiry into the nature of frequency distributions representative of multiple happenings with particular reference to the occurence of multiple attacks of disease or of repeated accidents, J. Roy. Statist. Soc. Ser. A, 83, 255–279.
Haight, Frank A. (1967). Handbook of the Poisson Distribution, Wiley, New York.
Johnson, N. L., Kotz, S. and Kemp, A. W. (1992). Univariate Discrete Distributions, Wiley, New York.
Kendall, M. G. (1961). Natural law in social sciences, J. Roy. Statist. Soc. Ser. A, 124, 1–19.
Kendall, M. and Stuart, A. (1979). The Advanced Theory of Statistics, Macmillan, New York.
Letac, G. (1992). Lectures on Natural Exponential Families and Their Variance Functions, Instituto de Matemática Pura y Aplicada, Rio de Janeiro.
McCullagh, P. and Nelder, J. A. (1989). Generalized Linear Models, 2nd ed., University Press, Cambridge.
Nelder, J. A. and Wedderburn, R. W. M. (1972). Generalized linear models, J. Roy. Statis. Soc. Ser. A. 135, 370–384.
Patil, G. P. and Rao, C. R. (1978). Weighted distributions ans size-biased sampling with applications to wildlife populations and human families, Biometrics, 34, 179–189.
Patil, G. P., Rao, C. R. and Ratnaparkhi, M. V. (1986). On discrete weighted distributions and their use in model for observed data, Communication in Statistics Theory and Methods, 15(3), 907–918.
Rao, C. R. (1965). On discrete distributions arising out of methods of ascertainment, Sankhyā Ser. A, 311–324.
Rao, C. R. (1973). Linear Statistical Inference and Its Applications, Wiley, New York.
Ross, S. M. (1983). Stochastic Processes, Wiley, New York.
Wolfram, S. (1991). Mathematica. A System for Doing Mathematics by Computer, Addison-Wesley, New York.
Author information
Authors and Affiliations
About this article
Cite this article
Del Castillo, J., Pérez-Casany, M. Weighted Poisson Distributions for Overdispersion and Underdispersion Situations. Annals of the Institute of Statistical Mathematics 50, 567–585 (1998). https://doi.org/10.1023/A:1003585714207
Issue Date:
DOI: https://doi.org/10.1023/A:1003585714207