Hot topics in polymer science in the recent years and decades included macromolecular
engineering enabled by controlled and living polymerization, use of polymers in biomedical …

The paper presents a Bayesian analysis of the multivariate Poisson distribution, based on
Gibbs sampling with data augmentation. This computational approach to the Bayesian …

Multi-dimensional data frequently occur in many different fields, including risk management,
insurance, biology, environmental sciences, and many more. In analyzing multivariate data …

The health profile of Southeast Sulawesi Province in 2021 shows that the prevalence of
stunting is 11.69%, wasting 5.89% and underweight 7.67%. This relatively high figure …

The bivariate Poisson distribution is commonly used to model bivariate count data. In this
paper we study a goodness-of-fit test for this distribution. We also provide a review of the …

Multivariate count data arise naturally in practice. In analysing such data, it is critical to
define a model that can accurately capture the underlying dependence structure between …

A four-parameter trivariate Poisson distribution was considered by Loukas and
Papageorgiou [6] where various properties of the distribution were examined and the …

A bivariate distribution is introduced with marginals convolutions of a binomial and a
Poisson random variables. Various properties of the distribution are examined. Estimation is …

In this report, we develop a procedure to analyze the relationship between the ob-served
multi-dimensional counts and a set of explanatory variables. The counts follow a multivariate …

Multivariate Poisson regression (MPR) is a statistical technique that is used to modeling of
relationships between two or more respon variables (Poisson distribution) and one or more …