Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/71196
題名: | Robust Regression Diagnostics With Data Transformations | 作者: | 鄭宗記 Cheng,Tsung-Chi |
貢獻者: | 統計系 | 日期: | 2005 | 上傳時間: | 6-Nov-2014 | 摘要: | The problems of non-normality or functional relationships between variables may often be simplified by an appropriate transformation. However, the evidence for transformations may sometimes depend crucially on one or a few observations. Therefore, the purpose of the paper is to develop a method that will not be influenced by potential outliers during the process of data transformations. The concepts of the least trimmed squares estimator and the trimmed likelihood estimator are used to obtain the robust transformation parameters. Furthermore, the proposed procedure unifies robust statistics and a diagnostic approach to deal with the outlier problem in the regression transformation. | 關聯: | Computational Statistics and Data Analysis49(6),875-891 | 資料類型: | article | DOI: | http://dx.doi.org/10.1016/j.csda.2004.06.010 |
Appears in Collections: | 期刊論文 |
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