Exponentiated-exponential geometric regression model

Felix Famoye, Carl Lee

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

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
Volume44
Issue number16
DOIs
StatePublished - Dec 10 2017

Keywords

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

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