Exponentiated-exponential geometric regression model

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.

KEYWORDS:

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

Acknowledgements

The authors are grateful for the comments and suggestions by the anonymous referees. These comments and suggestions have greatly improved the article.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Felix Famoye http://orcid.org/0000-0002-2286-6214

Additional information

Funding

The first author acknowledges the support from the Carnegie African Diaspora Fellowship Program [grant number 15410172].