Stationary birth-death processes generating inflation-deflation distributions: Avoiding the issue of dominance

TL;DR

This paper explores stationary distributions from modified birth-death processes, introducing two types of inflation-deflation distributions that form an exponential family, to better understand excess count phenomena.

Contribution

It directly examines the mechanisms behind excess counts by analyzing modified birth-death processes, providing a new perspective on inflation-deflation distributions.

Findings

Identifies two types of inflation-deflation stationary distributions.

Clarifies the distinction between mixture distributions and birth-death process mechanisms.

Highlights the importance of process modifications in modeling excess counts.

Abstract

A mixture of two or more count distributions has become deeply embedded in the analysis of excess counts, often relative to the stationary (equilibrium) distributions of birth-death processes such as the geometric, Poisson, Poisson-Lindley (PL), negative binomial (NB), hyper-Poisson (HP), and Conway-Maxwell-Poisson (CMP) distributions. However, the mechanism by which excess counts arise--namely, through modifications of the birth and death rates in the base distributions--has not yet been directly examined in the research literature. All well-known inflation mixture distributions are, in fact, parameterizations of the stationary distributions of birth-death processes. Thus, although the resulting distributions share the same shapes, they arise from distinct mechanisms and are not equivalent in regression analyses. This paper focuses on inflation-deflation stationary distributions arising from modified birth-death processes that form an exponential family and introduces two types of such distributions.