A New Ridge-Type Estimator for the Gamma Regression Model
The known linear regression model (LRM) is used mostly for modelling the QSAR relationship between the response variable (biological activity) and one or more physiochemical or structural properties which serve as the explanatory variables mainly when the distribution of the response variable is nor...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Scientifica |
| Online Access: | http://dx.doi.org/10.1155/2021/5545356 |
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| author | Adewale F. Lukman Issam Dawoud B. M. Golam Kibria Zakariya Y. Algamal Benedicta Aladeitan |
| author_facet | Adewale F. Lukman Issam Dawoud B. M. Golam Kibria Zakariya Y. Algamal Benedicta Aladeitan |
| author_sort | Adewale F. Lukman |
| collection | DOAJ |
| description | The known linear regression model (LRM) is used mostly for modelling the QSAR relationship between the response variable (biological activity) and one or more physiochemical or structural properties which serve as the explanatory variables mainly when the distribution of the response variable is normal. The gamma regression model is employed often for a skewed dependent variable. The parameters in both models are estimated using the maximum likelihood estimator (MLE). However, the MLE becomes unstable in the presence of multicollinearity for both models. In this study, we propose a new estimator and suggest some biasing parameters to estimate the regression parameter for the gamma regression model when there is multicollinearity. A simulation study and a real-life application were performed for evaluating the estimators' performance via the mean squared error criterion. The results from simulation and the real-life application revealed that the proposed gamma estimator produced lower MSE values than other considered estimators. |
| format | Article |
| id | doaj-art-270cffc8ed8d47639e205c66731835ed |
| institution | Kabale University |
| issn | 2090-908X |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Scientifica |
| spelling | doaj-art-270cffc8ed8d47639e205c66731835ed2025-02-03T07:23:31ZengWileyScientifica2090-908X2021-01-01202110.1155/2021/55453565545356A New Ridge-Type Estimator for the Gamma Regression ModelAdewale F. Lukman0Issam Dawoud1B. M. Golam Kibria2Zakariya Y. Algamal3Benedicta Aladeitan4Department of Physical Sciences, Landmark University, Omu-Aran, NigeriaDepartment of Mathematics, Al-Aqsa University, Gaza, State of PalestineDepartment of Mathematics and Statistics, Florida International University, Miami, FL 33199, USADepartment of Statistics and Informatics, University of Mosul, Mosul, IraqDepartment of Physical Sciences, Landmark University, Omu-Aran, NigeriaThe known linear regression model (LRM) is used mostly for modelling the QSAR relationship between the response variable (biological activity) and one or more physiochemical or structural properties which serve as the explanatory variables mainly when the distribution of the response variable is normal. The gamma regression model is employed often for a skewed dependent variable. The parameters in both models are estimated using the maximum likelihood estimator (MLE). However, the MLE becomes unstable in the presence of multicollinearity for both models. In this study, we propose a new estimator and suggest some biasing parameters to estimate the regression parameter for the gamma regression model when there is multicollinearity. A simulation study and a real-life application were performed for evaluating the estimators' performance via the mean squared error criterion. The results from simulation and the real-life application revealed that the proposed gamma estimator produced lower MSE values than other considered estimators.http://dx.doi.org/10.1155/2021/5545356 |
| spellingShingle | Adewale F. Lukman Issam Dawoud B. M. Golam Kibria Zakariya Y. Algamal Benedicta Aladeitan A New Ridge-Type Estimator for the Gamma Regression Model Scientifica |
| 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 |
| url | http://dx.doi.org/10.1155/2021/5545356 |
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