Performance of Alternative Estimators in the Poisson-Inverse Gaussian Regression Model: Simulation and Application

Abstract

The study proposed and compared the biased estimators for the Poisson-Inverse Gaussian regression model to deal with correlated regressors. The limitations of each biased estimator are also discussed. Additionally, some biasing parameters for the Stein estimator are proposed. The performance of estimators is evaluated with the help of a simulation study and a real-life application based on the minimum mean squared error criterion. The simulation and application findings favor the ridge estimator with specific biasing parameters because it provides less variation than others.

Keywords

• count data
• liu estimator
• maximum likelihood estimator
• multicollinearity
• poisson-inverse gaussian regression
• overdispersion
• ridge estimator
• stein estimator
• 62j07
• 62j12