A Modified Two Parameter Estimator with Different Forms of Biasing Parameters in the Linear Regression Model
Despite its common usage in estimating the linear regression model parameters, the ordinary least squares estimator often suffers a breakdown when two or more predictor variables are strongly correlated. This study proposes an alternative estimator to the OLS and other existing ridge-type estimator...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nigerian Society of Physical Sciences
2022-12-01
|
| Series: | African Scientific Reports |
| Subjects: | |
| Online Access: | https://asr.nsps.org.ng/index.php/asr/article/view/62 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849420985970720768 |
|---|---|
| author | Abiola T. Owolabi Kayode Ayinde Olusegun O. Alabi |
| author_facet | Abiola T. Owolabi Kayode Ayinde Olusegun O. Alabi |
| author_sort | Abiola T. Owolabi |
| collection | DOAJ |
| description |
Despite its common usage in estimating the linear regression model parameters, the ordinary least squares estimator often suffers a breakdown when two or more predictor variables are strongly correlated. This study proposes an alternative estimator to the OLS and other existing ridge-type estimators to tackle the problem of correlated regressors (multicollinearity). The properties of the proposed estimator were derived, and six forms of biasing parameter k (generalized, median, mid-range, arithmetic, harmonic and geometric means) were used in the proposed estimator to compare its performance with five other existing estimators through a simulation study. The proposed estimator dominated existing estimators when the mid-range, arithmetic mean, and median versions of k were used. However, the proposed estimator did not perform well when the generalized, harmonic, and geometric
mean versions were used.
|
| format | Article |
| id | doaj-art-3481ef5410e8409e9e7bbf26872d9d43 |
| institution | Kabale University |
| issn | 2955-1625 2955-1617 |
| language | English |
| publishDate | 2022-12-01 |
| publisher | Nigerian Society of Physical Sciences |
| record_format | Article |
| series | African Scientific Reports |
| spelling | doaj-art-3481ef5410e8409e9e7bbf26872d9d432025-08-20T03:31:34ZengNigerian Society of Physical SciencesAfrican Scientific Reports2955-16252955-16172022-12-011310.46481/asr.2022.1.3.6262A Modified Two Parameter Estimator with Different Forms of Biasing Parameters in the Linear Regression ModelAbiola T. OwolabiKayode AyindeOlusegun O. Alabi Despite its common usage in estimating the linear regression model parameters, the ordinary least squares estimator often suffers a breakdown when two or more predictor variables are strongly correlated. This study proposes an alternative estimator to the OLS and other existing ridge-type estimators to tackle the problem of correlated regressors (multicollinearity). The properties of the proposed estimator were derived, and six forms of biasing parameter k (generalized, median, mid-range, arithmetic, harmonic and geometric means) were used in the proposed estimator to compare its performance with five other existing estimators through a simulation study. The proposed estimator dominated existing estimators when the mid-range, arithmetic mean, and median versions of k were used. However, the proposed estimator did not perform well when the generalized, harmonic, and geometric mean versions were used. https://asr.nsps.org.ng/index.php/asr/article/view/62Ridge estimator, Liu estimator, Multicollinearity, Mean square error, Kibria-Lukman estimator, Prior iInformation |
| spellingShingle | Abiola T. Owolabi Kayode Ayinde Olusegun O. Alabi A Modified Two Parameter Estimator with Different Forms of Biasing Parameters in the Linear Regression Model African Scientific Reports Ridge estimator, Liu estimator, Multicollinearity, Mean square error, Kibria-Lukman estimator, Prior iInformation |
| title | A Modified Two Parameter Estimator with Different Forms of Biasing Parameters in the Linear Regression Model |
| title_full | A Modified Two Parameter Estimator with Different Forms of Biasing Parameters in the Linear Regression Model |
| title_fullStr | A Modified Two Parameter Estimator with Different Forms of Biasing Parameters in the Linear Regression Model |
| title_full_unstemmed | A Modified Two Parameter Estimator with Different Forms of Biasing Parameters in the Linear Regression Model |
| title_short | A Modified Two Parameter Estimator with Different Forms of Biasing Parameters in the Linear Regression Model |
| title_sort | modified two parameter estimator with different forms of biasing parameters in the linear regression model |
| topic | Ridge estimator, Liu estimator, Multicollinearity, Mean square error, Kibria-Lukman estimator, Prior iInformation |
| url | https://asr.nsps.org.ng/index.php/asr/article/view/62 |
| work_keys_str_mv | AT abiolatowolabi amodifiedtwoparameterestimatorwithdifferentformsofbiasingparametersinthelinearregressionmodel AT kayodeayinde amodifiedtwoparameterestimatorwithdifferentformsofbiasingparametersinthelinearregressionmodel AT olusegunoalabi amodifiedtwoparameterestimatorwithdifferentformsofbiasingparametersinthelinearregressionmodel AT abiolatowolabi modifiedtwoparameterestimatorwithdifferentformsofbiasingparametersinthelinearregressionmodel AT kayodeayinde modifiedtwoparameterestimatorwithdifferentformsofbiasingparametersinthelinearregressionmodel AT olusegunoalabi modifiedtwoparameterestimatorwithdifferentformsofbiasingparametersinthelinearregressionmodel |