On a robust estimator in heteroscedastic regression model in the presence of outliers
The ordinary least squares (OLS) procedure is inefficient when the underlying assumption of constant error variances (homoscedasticity) is not met. As an alternative, we often used weighted least squares (WLS) procedure which requires a known form of the heteroscedastic errors structures, to estimat...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
International Association of Engineers (IAENG)
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/41350/ http://psasir.upm.edu.my/id/eprint/41350/1/41350.pdf |
| _version_ | 1848849672289910784 |
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| author | Midi, Habshah Rana, Sohel Imon, A. H. M. R. |
| author_facet | Midi, Habshah Rana, Sohel Imon, A. H. M. R. |
| author_sort | Midi, Habshah |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The ordinary least squares (OLS) procedure is inefficient when the underlying assumption of constant error variances (homoscedasticity) is not met. As an alternative, we often used weighted least squares (WLS) procedure which requires a known form of the heteroscedastic errors structures, to estimate the regression parameters when heteroscedasticity occurs in the data. It is now evident that the WLS estimator is easily affected by outliers. To remedy the problem of heteroscedasticity and outliers simultaneously, we proposed a new method that we call two-step robust weighted least squares (TSRWLS) where prior information on the structure of the heteroscedastic errors is not required. The performance of the newly proposed estimator is investigated extensively by real data sets and Monte Carlo simulations. |
| first_indexed | 2025-11-15T09:54:07Z |
| format | Conference or Workshop Item |
| id | upm-41350 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T09:54:07Z |
| publishDate | 2013 |
| publisher | International Association of Engineers (IAENG) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-413502015-11-05T09:20:48Z http://psasir.upm.edu.my/id/eprint/41350/ On a robust estimator in heteroscedastic regression model in the presence of outliers Midi, Habshah Rana, Sohel Imon, A. H. M. R. The ordinary least squares (OLS) procedure is inefficient when the underlying assumption of constant error variances (homoscedasticity) is not met. As an alternative, we often used weighted least squares (WLS) procedure which requires a known form of the heteroscedastic errors structures, to estimate the regression parameters when heteroscedasticity occurs in the data. It is now evident that the WLS estimator is easily affected by outliers. To remedy the problem of heteroscedasticity and outliers simultaneously, we proposed a new method that we call two-step robust weighted least squares (TSRWLS) where prior information on the structure of the heteroscedastic errors is not required. The performance of the newly proposed estimator is investigated extensively by real data sets and Monte Carlo simulations. International Association of Engineers (IAENG) 2013 Conference or Workshop Item NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/41350/1/41350.pdf Midi, Habshah and Rana, Sohel and Imon, A. H. M. R. (2013) On a robust estimator in heteroscedastic regression model in the presence of outliers. In: World Congress on Engineering 2013, 3-5 July 2013, London, United Kingdom. (pp. 280-285). http://www.iaeng.org/publication/WCE2013/WCE2013_pp280-285.pdf |
| spellingShingle | Midi, Habshah Rana, Sohel Imon, A. H. M. R. On a robust estimator in heteroscedastic regression model in the presence of outliers |
| title | On a robust estimator in heteroscedastic regression model in the presence of outliers |
| title_full | On a robust estimator in heteroscedastic regression model in the presence of outliers |
| title_fullStr | On a robust estimator in heteroscedastic regression model in the presence of outliers |
| title_full_unstemmed | On a robust estimator in heteroscedastic regression model in the presence of outliers |
| title_short | On a robust estimator in heteroscedastic regression model in the presence of outliers |
| title_sort | on a robust estimator in heteroscedastic regression model in the presence of outliers |
| url | http://psasir.upm.edu.my/id/eprint/41350/ http://psasir.upm.edu.my/id/eprint/41350/ http://psasir.upm.edu.my/id/eprint/41350/1/41350.pdf |