Biparametric zero-modified power series distributions: Bayesian analysis under a reference prior approach

This paper presents a Bayesian approach by considering a reference prior for estimating the parameters of biparametric zero-modified power series (ZMPS) distributions. The ZMPS distribution is an extension of the power series (PS) distribution family, allowing it to be adjusted to count data without previous knowledge of frequency of zero observations in the sample (e.g., zero-inflated or zero-deflated datasets). Simulation studies are presented in order to illustrate the performance of the proposed methodology. Applications of the proposed methodology involve the analysis of three real datasets.