The Poisson regression model (PRM) is a widely used statistical technique for analyzing
count data. However, when explanatory variables in the model are correlated, the estimation …

This study introduces a new two-parameter Liu estimator (PMTPLE) for addressing the
multicollinearity problem in the Poisson regression model (PRM). The estimation of the PRM …

Abstract The extended Poisson-Tweedie (EPT) regression model is one of the count data
regression models. It's a more flexible model in count data; since EPT model can be used in …

Poisson and negative binomial regressions are popular methods for modelling the
relationship between a count variable and explanatory variables. In the presence of …

The logistic regression model is one of the most powerful statistical methods for the analysis
of binary data. Logistic regression allows using a set of covariates to explain the binary …

Zero-inflated Poisson (ZIP) model is widely used for counting data with excessive zeroes.
The multicollinearity is the common factor in the explanatory variables of the count data. In …

In the analysis of logistic regression models, various biased estimators have been proposed
as an alternative to the maximum likelihood estimator (MLE) for estimating model …

One of the most important models for the analysis of count data is the Poisson Regression
Model (PRM). The parameter estimates of the PRM are obtained by the Maximum Likelihood …