A New Ridge-Type Estimator for the Gamma regression model
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 curren...
| الحاوية / القاعدة: | Iraqi Journal for Computer Science and Mathematics |
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| المؤلفون الرئيسيون: | , , |
| التنسيق: | مقال |
| اللغة: | الإنجليزية |
| منشور في: |
College of Education, Al-Iraqia University
2024-01-01
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://journal.esj.edu.iq/index.php/IJCM/article/view/812 |
| الملخص: | 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
estimators under 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 that the proposed estimator is superior to competing estimators.
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| تدمد: | 2958-0544 2788-7421 |