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...
| Published in: | Iraqi Journal for Computer Science and Mathematics |
|---|---|
| Main Authors: | , , |
| Format: | Article |
| Language: | English |
| Published: |
College of Education, Al-Iraqia University
2024-01-01
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| Subjects: | |
| Online Access: | https://journal.esj.edu.iq/index.php/IJCM/article/view/812 |
| _version_ | 1850002149594890240 |
|---|---|
| author | Ahmed Maher Salih Zakariya Algamal Mundher Abdullah Khaleel |
| author_facet | Ahmed Maher Salih Zakariya Algamal Mundher Abdullah Khaleel |
| author_sort | Ahmed Maher Salih |
| collection | DOAJ |
| container_title | Iraqi Journal for Computer Science and Mathematics |
| description |
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.
|
| format | Article |
| id | doaj-art-e2e647093ce8464ea0b1ffe23f8ebeb3 |
| institution | Directory of Open Access Journals |
| issn | 2958-0544 2788-7421 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | College of Education, Al-Iraqia University |
| record_format | Article |
| spelling | doaj-art-e2e647093ce8464ea0b1ffe23f8ebeb32025-08-20T00:48:32ZengCollege of Education, Al-Iraqia UniversityIraqi Journal for Computer Science and Mathematics2958-05442788-74212024-01-015110.52866/ijcsm.2024.05.01.006A New Ridge-Type Estimator for the Gamma regression modelAhmed Maher Salih0Zakariya Algamal1Mundher Abdullah Khaleel2Department of Mathematics , University of Tikrit, Tikrit, IraqUniversity of MosulDepartment of Mathematics , University of Tikrit, Tikrit, Iraq 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. https://journal.esj.edu.iq/index.php/IJCM/article/view/812Multicollinearityridge estimatorgamma regression modelLiu-type estimatorMonte Carlo simulation |
| spellingShingle | Ahmed Maher Salih Zakariya Algamal Mundher Abdullah Khaleel A New Ridge-Type Estimator for the Gamma regression model Multicollinearity ridge estimator gamma regression model Liu-type estimator Monte Carlo simulation |
| title | A New Ridge-Type Estimator for the Gamma regression model |
| title_full | A New Ridge-Type Estimator for the Gamma regression model |
| title_fullStr | A New Ridge-Type Estimator for the Gamma regression model |
| title_full_unstemmed | A New Ridge-Type Estimator for the Gamma regression model |
| title_short | A New Ridge-Type Estimator for the Gamma regression model |
| title_sort | new ridge type estimator for the gamma regression model |
| topic | Multicollinearity ridge estimator gamma regression model Liu-type estimator Monte Carlo simulation |
| url | https://journal.esj.edu.iq/index.php/IJCM/article/view/812 |
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