This study proposes new statistical tools to analyze the counts of the daily coronavirus cases
and deaths. Since the daily new deaths exhibit highly over-dispersion, we introduce a new …

This study introduces the Poisson-Bilal distribution and its associated two models for
modeling the over-dispersed count data sets. The Poisson-Bilal distribution has tractable …

In this study, a new one-parameter discrete distribution obtained by compounding the
Poisson and xgamma distributions is proposed. Some statistical properties of the new …

This article presents the Poisson-Inverse Gamma regression model with varying dispersion
for approximating heavy-tailed and overdispersed claim counts. Our main contribution is that …

Objectives The study aimed to (1) determine the incidence and gender-specific risk ratio of
acute on-snow severe injury events (SIE) in elite alpine ski racing,(2) examine the …

In this article, we propose the discrete version of the binomial exponential II distribution for
modelling count data. Some of its statistical properties including hazard rate function, mode …

Several research investigations have stressed the importance of discrete data analysis and
its relevance to actual events. The current work focuses on a new discrete distribution with a …

Count regression models are important statistical tools to model the discrete dependent
variable with known covariates. When the dependent variable exhibits over-dispersion and …

Count data regression is one of the widely used techniques for modelling medical data and
has applications in various other fields as well. Count data usually exhibits the characteristic …

Machine learning algorithms, especially random forests (RFs), have become an integrated
part of the modern scientific methodology and represent an efficient alternative to …