| Автор | Simpsona, James R. |
| Автор | Montgomery, Douglas C. |
| Дата выпуска | 1996 |
| dc.description | The combined outlier-multicollinearity problem occurs frequently in regression data. Methods that successfully address this problem effectively combine biased and robust estimation techniques. A biased-robust estimator is proposed that uses a multi-stage generalized M-estimator with fully iterated ridge regression to successfully control both influence and coUinearity in regression datasets. Two previously published approaches are compared with the proposal via simulation experiments. The best performing published technique is also compared with our proposal using a dataset containing a cloud of outliers and severe multicollinearity. The proposed biased-robust method outperforms the published technique both in simulation and the example. |
| Формат | application.pdf |
| Издатель | Gordon and Breach Science Publishers |
| Копирайт | Copyright Taylor and Francis Group, LLC |
| Тема | Montecarlo simulation |
| Тема | ridge regression |
| Тема | breakdown point |
| Тема | efficiency |
| Тема | bounded influence |
| Название | A biased-robust regression technique for the combined outlier-multicollinearity problem |
| Тип | research-article |
| DOI | 10.1080/00949659608811777 |
| Electronic ISSN | 1563-5163 |
| Print ISSN | 0094-9655 |
| Журнал | Journal of Statistical Computation and Simulation |
| Том | 56 |
| Первая страница | 1 |
| Последняя страница | 22 |
| Аффилиация | Simpsona, James R.; Department of Mathematical Sciences, United States Air Force Academy |
| Аффилиация | Montgomery, Douglas C.; Department of Industrial and Management Systems Engineering, Arizona State University |
| Выпуск | 1 |
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