Statistics and Its Interface

Volume 9 (2016)

Number 1

Properties of the zero-and-one inflated Poisson distribution and likelihood-based inference methods

Pages: 11 – 32

DOI: https://dx.doi.org/10.4310/SII.2016.v9.n1.a2

Authors

Chi Zhang (Department of Statistics and Actuarial Science, University of Hong Kong)

Guo-Liang Tian (Department of Statistics and Actuarial Science, University of Hong Kong)

Kai-Wang Ng (Department of Statistics and Actuarial Science, University of Hong Kong)

Abstract

To model count data with excess zeros and excess ones, in their unpublished manuscript, Melkersson and Olsson (1999) extended the zero-inflated Poisson distribution to a zero-and-one-inflated Poisson (ZOIP) distribution. However, the distributional theory and corresponding properties of the ZOIP have not yet been explored, and likelihood-based inference methods for parameters of interest were not well developed. In this paper, we extensively study the ZOIP distribution by first constructing five equivalent stochastic representations for the ZOIP random variable and then deriving other important distributional properties. Maximum likelihood estimates of parameters are obtained by both the Fisher scoring and expectation—maximization algorithms. Bootstrap confidence intervals for parameters of interest and testing hypotheses under large sample sizes are provided. Simulations studies are performed and five real data sets are used to illustrate the proposed methods.

Keywords

EM algorithm, Fisher scoring algorithm, one-inflated Poisson distribution, zero-inflated Poisson model, zero-and-one inflated Poisson model

Published 22 October 2015