The prequel to this review provided an extensive treatment of classic zero‐inflated count
regression models where a univariate discrete distribution is used for the count regression …

The objective of this study was to develop a novel copula-based time series (CTS) model to
forecast COVID-19 cases and trends based on wastewater SARS-CoV-2 viral load and …

A class of bivariate integer-valued time series models was constructed via copula theory.
Each series follows a Markov chain with the serial dependence captured using copula …

The ability of government agencies to assign accurate ages of fish is important to fisheries
management. Accurate ageing allows for most reliable age‐based models to be used to …

The class of bivariate integer-valued time series models, described via copula theory, is
gaining popularity in the literature because of applications in health sciences, engineering …

Short-window crash prediction is a fundamental step in proactive traffic safety management
that can monitor traffic conditions in real time, identify unsafe traffic dynamics, and implement …

A first-order autoregressive time series model with binomial distributed random variables
has been developed using the copula-based Markov chain model approach. By still utilizing …

The Poisson point process plays a pivotal role in modeling spatial point patterns. One of its
key features is that the variance and the mean of the total number of points in a given region …

In this paper, a new multivariate zero-inflated binomial (MZIB) distribution is proposed to
analyse the correlated proportional data with excessive zeros. The distributional properties …

Several scientific observations produce data that consist of serially dependent counts that
are difficult to accurately analyze due to the absence of normality and the limited literature …