Recently, although advances were made on modeling multivariate count data, existing
models really has several limitations:(i) The multivariate Poisson log‐normal model …

To model count data with excess zeros, ones and twos, for the first time we introduce a so-
called zero-one-two-inflated Poisson (ZOTIP) distribution, including the zero-inflated …

This paper extends the univariate zero-and-one inflated Poisson (ZOIP) distribution
(Melkersson & Olsson, 1999; Zhang et al., 2016) to its multivariate version, which can be …

Excessive zeros in multivariate count data are often observed in scenarios of biomedicine
and public health. To provide a better analysis on this type of data, we first develop a …

Excessive zeros in multivariate count data are often encountered in practice. Since the
Poisson distribution only possesses the property of equi-dispersion, the existing Type I …

Count data often arise in biomedical studies, while there could be a special feature with
excessive zeros in the observed counts. The zero‐inflated Poisson model provides a natural …

Count data with excess zeros are widely encountered in the fields of biomedical, medical,
public health and social survey, etc. Zero-inflated Poisson (ZIP) regression models with …

To model count data with excess zeros and excess ones, in their unpublished manuscript,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 …

Count data are collected repeatedly over time in many applications, such as biology,
epidemiology, and public health. Such data are often characterized by the following three …

Multivariate zero‐inflated Poisson (ZIP) distributions are important tools for modelling and
analysing correlated count data with extra zeros. Unfortunately, existing multivariate ZIP …