Estimation parameters using bisquare weighted robust ridge regression BRLTS estimator in the presence of multicollinearity and outliers
This study presents an improvement to robust ridge regression estimator. We proposed two methods Bisquare ridge least trimmed squares (BRLTS) and Bisquare ridge least absolute value (BRLAV) based on ridge least trimmed squares RLTS and ridge least absolute value (RLAV) respectively. We compared thes...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.utm.my/61313/1/RobiahAdnan2015_EstimationParametersUsingBisquareWeighted.pdf |
| _version_ | 1796861078811967488 |
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| author | Kafi, Dano Pati Adnan, Robiah Rasheed, Abdulkadir Bello Md. Jedi, Muhamad Alias |
| author_facet | Kafi, Dano Pati Adnan, Robiah Rasheed, Abdulkadir Bello Md. Jedi, Muhamad Alias |
| author_sort | Kafi, Dano Pati |
| collection | ePrints |
| description | This study presents an improvement to robust ridge regression estimator. We proposed two methods Bisquare ridge least trimmed squares (BRLTS) and Bisquare ridge least absolute value (BRLAV) based on ridge least trimmed squares RLTS and ridge least absolute value (RLAV) respectively. We compared these methods with existing estimators, namely ordinary least squares (OLS) and Bisquare ridge regression (BRID) using three criteria: Bias, Root Mean Square Error (RMSE) and Standard Error (SE) to estimate the parameters coe±cients. The results of Bisquare ridge least trimmed squares (BRLTS) and Bisquare ridge least absolute value (BRLAV) are compared with existing methods using real data and simulation study. The empirical evidence shows that the results obtain from the BRLTS are the best among the three estimators followed by BRLAV with the least value of the RMSE for the diÆerent disturbance distributions and degrees of multicollinearity. |
| first_indexed | 2024-03-05T19:50:56Z |
| format | Conference or Workshop Item |
| id | utm.eprints-61313 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T19:50:56Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | utm.eprints-613132017-07-31T07:03:03Z http://eprints.utm.my/61313/ Estimation parameters using bisquare weighted robust ridge regression BRLTS estimator in the presence of multicollinearity and outliers Kafi, Dano Pati Adnan, Robiah Rasheed, Abdulkadir Bello Md. Jedi, Muhamad Alias QA Mathematics This study presents an improvement to robust ridge regression estimator. We proposed two methods Bisquare ridge least trimmed squares (BRLTS) and Bisquare ridge least absolute value (BRLAV) based on ridge least trimmed squares RLTS and ridge least absolute value (RLAV) respectively. We compared these methods with existing estimators, namely ordinary least squares (OLS) and Bisquare ridge regression (BRID) using three criteria: Bias, Root Mean Square Error (RMSE) and Standard Error (SE) to estimate the parameters coe±cients. The results of Bisquare ridge least trimmed squares (BRLTS) and Bisquare ridge least absolute value (BRLAV) are compared with existing methods using real data and simulation study. The empirical evidence shows that the results obtain from the BRLTS are the best among the three estimators followed by BRLAV with the least value of the RMSE for the diÆerent disturbance distributions and degrees of multicollinearity. 2015 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/61313/1/RobiahAdnan2015_EstimationParametersUsingBisquareWeighted.pdf Kafi, Dano Pati and Adnan, Robiah and Rasheed, Abdulkadir Bello and Md. Jedi, Muhamad Alias (2015) Estimation parameters using bisquare weighted robust ridge regression BRLTS estimator in the presence of multicollinearity and outliers. In: Simposium Kebangsaan Sains Matematik ke-23, 24-26 Nov, 2015, Johor Bahru, Johor. |
| spellingShingle | QA Mathematics Kafi, Dano Pati Adnan, Robiah Rasheed, Abdulkadir Bello Md. Jedi, Muhamad Alias Estimation parameters using bisquare weighted robust ridge regression BRLTS estimator in the presence of multicollinearity and outliers |
| title | Estimation parameters using bisquare weighted robust ridge regression BRLTS estimator in the presence of multicollinearity and outliers |
| title_full | Estimation parameters using bisquare weighted robust ridge regression BRLTS estimator in the presence of multicollinearity and outliers |
| title_fullStr | Estimation parameters using bisquare weighted robust ridge regression BRLTS estimator in the presence of multicollinearity and outliers |
| title_full_unstemmed | Estimation parameters using bisquare weighted robust ridge regression BRLTS estimator in the presence of multicollinearity and outliers |
| title_short | Estimation parameters using bisquare weighted robust ridge regression BRLTS estimator in the presence of multicollinearity and outliers |
| title_sort | estimation parameters using bisquare weighted robust ridge regression brlts estimator in the presence of multicollinearity and outliers |
| topic | QA Mathematics |
| url | http://eprints.utm.my/61313/1/RobiahAdnan2015_EstimationParametersUsingBisquareWeighted.pdf |
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