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Some Remarks on the “Generalized Event Count” Distribution

  • John Londregan

Abstract

King (1989) presented the “Generalized Event Count” (GEC) model as a means of dealing with event count data when the analyst is unsure whether the data are “underdispersed” or “overdispersed.” Here I establish several useful properties of the GEC model and make some practical suggestions for estimation.

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References

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Hogg, Robert V., and Tanis, Elliot A. 1977. Probability and Statistical Inference. New York: Macmillan.
Katz, Leo. 1965. “Unified Treatment of a Broad Class of Discrete Probability Distributions.” In Classical and Contagious Discrete Distributions, edited by Patil, G. P. Calcutta: Statistical Publishing Society.
King, Gary. 1989. “Variance Specification in Event Count Models: From Restrictive Assumptions to a Generalized Estimator.” American Journal of Political Science 33: 762–84.
Winkelmann, R., Signorino, C., and King, G. 1994. “A Correction for the Underdispersed Event Count Probability Distribution.” Political Analysis 5: 215–28.
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