Proposed methods in estimating the ridge regression parameter in Poisson regression model

Poisson regression model is considered as an important model among the linear logarithm models. It is usually used to model the count dependent variable. However, as in linear regression model, the multicollinearity problem may be present leading to negatively affect the model parameter estimation. In this study, several methods are proposed to estimate the ridge parameter. Monte-Carlo simulation studies with different factors were conducted to evaluate the performance of the used estimators. The results demonstrate the better performance of the proposed estimator compared to other used estimators in terms of mean squared error (MSE).