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On the performance of two-parameter ridge estimators for handling multicollinearity problem in linear regression: Simulation and application.
- Source :
-
AIP Advances . Nov2023, Vol. 13 Issue 11, p1-13. 13p. - Publication Year :
- 2023
-
Abstract
- The inability of ordinary least square estimators against multicollinearity has paved the way for the development of various ridge-type estimators, which are recently classified as one-parameter and two-parameter ridge estimators. In this paper, we offer some efficient two-parameter ridge estimators and evaluate their performance through a simulation study by using the minimum mean square error criterion. Under most of the simulation conditions, our proposed estimators outperformed the existing estimators. Finally, two real-life datasets are used to demonstrate the applications of our proposed estimators. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MULTICOLLINEARITY
*MEAN square algorithms
*LEAST squares
Subjects
Details
- Language :
- English
- ISSN :
- 21583226
- Volume :
- 13
- Issue :
- 11
- Database :
- Academic Search Index
- Journal :
- AIP Advances
- Publication Type :
- Academic Journal
- Accession number :
- 173787287
- Full Text :
- https://doi.org/10.1063/5.0175494