Bayesian Analyses of Ridge Regression Prooblems
A Bayesian formulation of the ridge regression problem is considerd, which derives from a direct specification of prior informations about parameters of general linear regression model when data suffer from a high degree of multicollinearity.A new approach for deriving the conventional estimator...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
University of Baghdad
2017-05-01
|
| Series: | Ibn Al-Haitham Journal for Pure and Applied Sciences |
| Online Access: | https://jih.uobaghdad.edu.iq/index.php/j/article/view/898 |
| _version_ | 1828344211927203840 |
|---|---|
| author | H. M. Gorgees |
| author_facet | H. M. Gorgees |
| author_sort | H. M. Gorgees |
| collection | DOAJ |
| description |
A Bayesian formulation of the ridge regression problem is considerd, which derives from a direct specification of prior informations about parameters of general linear regression model when data suffer from a high degree of multicollinearity.A new approach for deriving the conventional estimator for the ridge parameter proposed by Hoerl and Kennard (1970) as well as Bayesian estimator are presented. A numerical example is studied in order to compare the performance of these estimators.
|
| first_indexed | 2024-04-13T23:53:10Z |
| format | Article |
| id | doaj.art-fe050656be304ef79a22b44d0e0d3e47 |
| institution | Directory Open Access Journal |
| issn | 1609-4042 2521-3407 |
| language | English |
| last_indexed | 2024-04-13T23:53:10Z |
| publishDate | 2017-05-01 |
| publisher | University of Baghdad |
| record_format | Article |
| series | Ibn Al-Haitham Journal for Pure and Applied Sciences |
| spelling | doaj.art-fe050656be304ef79a22b44d0e0d3e472022-12-22T02:24:00ZengUniversity of BaghdadIbn Al-Haitham Journal for Pure and Applied Sciences1609-40422521-34072017-05-01233Bayesian Analyses of Ridge Regression ProoblemsH. M. Gorgees A Bayesian formulation of the ridge regression problem is considerd, which derives from a direct specification of prior informations about parameters of general linear regression model when data suffer from a high degree of multicollinearity.A new approach for deriving the conventional estimator for the ridge parameter proposed by Hoerl and Kennard (1970) as well as Bayesian estimator are presented. A numerical example is studied in order to compare the performance of these estimators. https://jih.uobaghdad.edu.iq/index.php/j/article/view/898 |
| spellingShingle | H. M. Gorgees Bayesian Analyses of Ridge Regression Prooblems Ibn Al-Haitham Journal for Pure and Applied Sciences |
| title | Bayesian Analyses of Ridge Regression Prooblems |
| title_full | Bayesian Analyses of Ridge Regression Prooblems |
| title_fullStr | Bayesian Analyses of Ridge Regression Prooblems |
| title_full_unstemmed | Bayesian Analyses of Ridge Regression Prooblems |
| title_short | Bayesian Analyses of Ridge Regression Prooblems |
| title_sort | bayesian analyses of ridge regression prooblems |
| url | https://jih.uobaghdad.edu.iq/index.php/j/article/view/898 |
| work_keys_str_mv | AT hmgorgees bayesiananalysesofridgeregressionprooblems |