Zero-inflated models and estimation in zero-inflated Poisson distribution

ABSTRACT

In this paper, we briefly overview different zero-inflated probability distributions. We compare the performance of the estimates of Poisson, Generalized Poisson, ZIP, ZIGP and ZINB models through Mean square error (MSE), bias and Standard error (SE) when the samples are generated from ZIP distribution. We propose a new estimator referred to as probability estimator (PE) of inflation parameter of ZIP distribution based on moment estimator (ME) of the mean parameter and compare its performance with ME and maximum likelihood estimator (MLE) through a simulation study. We use the PE along with ME and MLE to fit ZIP distribution to various zero-inflated datasets and observe that the results do not differ significantly. We recommend using PE in place of MLE since it is easy to calculate and the simulation study in this paper demonstrates that the PE performs as good as MLE irrespective of the sample size.

KEYWORDS:

• Simulation
• Zero-inflated Poisson (ZIP)
• Zero-inflated Negative Binomial (ZINB)
• Zero-inflated generalized Poisson model (ZIGP)

Acknowledgment

The authors thank the referees for their useful comments and valuable suggestions which improved the presentation of work.