Combining modified ridge-type and principal component regression estimators
The performance of ordinary least squares estimator (OLSE) when there is multicollinearity (MC) in a linear regression model becomes inefficient. The principal components regression and the modified ridge-type estimator have been proposed at a different time to handle the problem of MC. However, in...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2020-09-01
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| Series: | Scientific African |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S246822762030274X |
| _version_ | 1819107533135020032 |
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| author | Adewale F. Lukman Kayode Ayinde Olajumoke Oludoun Clement A. Onate |
| author_facet | Adewale F. Lukman Kayode Ayinde Olajumoke Oludoun Clement A. Onate |
| author_sort | Adewale F. Lukman |
| collection | DOAJ |
| description | The performance of ordinary least squares estimator (OLSE) when there is multicollinearity (MC) in a linear regression model becomes inefficient. The principal components regression and the modified ridge-type estimator have been proposed at a different time to handle the problem of MC. However, in this paper, we developed a new estimator by combining these two estimators and derived the necessary and sufficient condition for its superiority over other competing estimators. Furthermore, we establish the dominance of this new estimator over other estimators through a simulation study, and numerical example in terms of the estimated mean squared error. |
| first_indexed | 2024-12-22T02:55:33Z |
| format | Article |
| id | doaj.art-9e6f37866ac142089d214bb97418baef |
| institution | Directory Open Access Journal |
| issn | 2468-2276 |
| language | English |
| last_indexed | 2024-12-22T02:55:33Z |
| publishDate | 2020-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Scientific African |
| spelling | doaj.art-9e6f37866ac142089d214bb97418baef2022-12-21T18:41:17ZengElsevierScientific African2468-22762020-09-019e00536Combining modified ridge-type and principal component regression estimatorsAdewale F. Lukman0Kayode Ayinde1Olajumoke Oludoun2Clement A. Onate3Department of Physical Sciences, Landmark University, Omu-Aran, Nigeria; Centre Emile Borel, Institut Henri Poincare, Paris, France; Corresponding author.Department of Statistics, Federal University of Technology, Akure, NigeriaDepartment of Physical Sciences, Landmark University, Omu-Aran, NigeriaDepartment of Physical Sciences, Landmark University, Omu-Aran, NigeriaThe performance of ordinary least squares estimator (OLSE) when there is multicollinearity (MC) in a linear regression model becomes inefficient. The principal components regression and the modified ridge-type estimator have been proposed at a different time to handle the problem of MC. However, in this paper, we developed a new estimator by combining these two estimators and derived the necessary and sufficient condition for its superiority over other competing estimators. Furthermore, we establish the dominance of this new estimator over other estimators through a simulation study, and numerical example in terms of the estimated mean squared error.http://www.sciencedirect.com/science/article/pii/S246822762030274XOLSEPrincipal componentModified ridge-typeCompeting estimators |
| spellingShingle | Adewale F. Lukman Kayode Ayinde Olajumoke Oludoun Clement A. Onate Combining modified ridge-type and principal component regression estimators Scientific African OLSE Principal component Modified ridge-type Competing estimators |
| title | Combining modified ridge-type and principal component regression estimators |
| title_full | Combining modified ridge-type and principal component regression estimators |
| title_fullStr | Combining modified ridge-type and principal component regression estimators |
| title_full_unstemmed | Combining modified ridge-type and principal component regression estimators |
| title_short | Combining modified ridge-type and principal component regression estimators |
| title_sort | combining modified ridge type and principal component regression estimators |
| topic | OLSE Principal component Modified ridge-type Competing estimators |
| url | http://www.sciencedirect.com/science/article/pii/S246822762030274X |
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