Exponentiated-exponential geometric regression model

Felix Famoye, Carl Lee

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


A regression model, based on the exponentiated-exponential geometric distribution, is defined and studied. The regression model can be applied to count data with under-dispersion or over-dispersion. Some forms of its modifications to truncated or inflated data are mentioned. Some tests to discriminate between the regression model and its competitors are discussed. Real numerical data sets are used to illustrate the applications of the regression model.

Original languageEnglish
Pages (from-to)2963-2977
Number of pages15
JournalJournal of Applied Statistics
Issue number16
StatePublished - Dec 10 2017


  • Count model
  • tests
  • under- and over-dispersion
  • zero-inflation


Dive into the research topics of 'Exponentiated-exponential geometric regression model'. Together they form a unique fingerprint.

Cite this