Abstract
When there is collinearity among the regressors in gamma regression models, we present a new two-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 the estimatorsunder various collinearity designs in terms of mean squared error, we run a Monte Carlo simulation analysis. We also offer a real data application to demonstrate the usefulness of the new estimator. The results from simulations and actual data reveal thatthe proposed estimator is superior to competing estimators.
Recommended Citation
Algamal, Zakariya Yahya; Salih, Ahmed Maher; and Khaleel, Mundher Abdullah
(2024)
"0544A New Ridge-Type Estimator for the Gamma regression model,"
Iraqi Journal for Computer Science and Mathematics: Vol. 5:
Iss.
1, Article 22.
DOI: https://doi.org/10.52866/ijcsm.2024.05.01.006
Available at:
https://ijcsm.researchcommons.org/ijcsm/vol5/iss1/22
