A New Ridge-Type Estimator for the Gamma regression model

Abstract

When there is collinearity among the regressors in gamma regression models, we present a newtwo-parameter ridge estimator in this study. We look into the new estimator's mean squared error characteristics.Additionally, we offer several theorems to contrast the new estimators with the current ones. To compare theestimators under various collinearity designs in terms of mean squared error, we run a Monte Carlo simulationanalysis. We also offer a real data application to demonstrate the usefulness of the new estimator. The results fromsimulations and actual data reveal that the proposed estimator is superior to competing estimators.