Skip to main content Accessibility help

Some Remarks on the “Generalized Event Count” Distribution

  • John Londregan


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.



Hide All
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.
MathJax is a JavaScript display engine for mathematics. For more information see


Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed