Bootstrap Liu estimators for Poisson regression model

Abstract

The Liu estimator is used to get precise estimatesby introducing bootstrap technique to reduce the problem of multicollinearity in Poisson regression model. In the presence of multicollinearity, the variance of maximum likelihood estimator (MLE) becomes overstated and theinference based on MLEdoes not remain trustworthy. In this article, we proposed some new Poisson bootstrap Liu and ridge estimators. The proposed estimators are then compared with the non-bootstrap Liu and ridge estimators. Based on mean-squared error criterion, the simulation study revealed showed that the proposed estimators showed efficient results as compared to other existing estimators. Finally, a real example is used to illustrate the application ofproposed estimators.

Keywords:

• Multicollinearity
• Poisson
• Liu
• Bootstrapping
• Maximum likelihood
• Ridge regression