Classical and Bayesian estimation of discrete poisson Agu-Eghwerido distribution with applications - Osama Abdulaziz Alamri (Alexandria Engineering Journal)
This study presents a novel single-parameter counting model that merges the Poisson distribution with the Agu-Eghwerido distribution. The newly developed model is referred to as the ''Poisson Agu-Eghwerido Distribution.'' We investigate major mathematical and statistical aspects of this distribution, including factorial moments, probability-generating, moment-generating, Shannon entropy, skewness, and kurtosis. The model parameter is estimated using a maximum likelihood estimation and Bayesian estimation approaches. We use Monte Carlo simulation to investigate the behavior of the estimators. Finally, we examine two real-world datasets to determine the effectiveness of the suggested distribution in representing count data. It is concluded that the new model analyzed these two datasets efficiently as compared to the competitive distributions.