| dc.contributor | 統計系 | |
| dc.creator (作者) | Cheng, Tsung-Chi;Biswas, Atanu | |
| dc.creator (作者) | 鄭宗記 | zh_TW |
| dc.date (日期) | 2008-01 | |
| dc.date.accessioned | 24-Aug-2015 15:00:37 (UTC+8) | - |
| dc.date.available | 24-Aug-2015 15:00:37 (UTC+8) | - |
| dc.date.issued (上傳時間) | 24-Aug-2015 15:00:37 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/77960 | - |
| dc.description.abstract (摘要) | In this article, we apply the maximum trimmed likelihood (MTL) approach [Hadi, A.S., Luceño, A., 1997. Maximum trimmed likelihood estimators: a unified approach, examples, and algorithms. Comput. Statist. Data Anal. 25, 251–272] to obtain the robust estimators of multivariate location and shape, especially for data mixed with continuous and categorical variables. The forward search algorithm [Atkinson, A.C., 1994. Fast very robust methods for the detection of multiple outliers. J. Amer. Statist. Assoc. 89, 1329–1339] is adapted to compute the proposed MTL estimates. A simulation study shows that the proposed estimator outperforms the classical maximum likelihood estimator when outliers exist in data. Real data sets are also used to illustrate the method and results of the detection of the outliers. | |
| dc.format.extent | 1446714 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Computational Statistics & Data Analysis, 52(4), 2042-2065 | |
| dc.subject (關鍵詞) | Forward search algorithm;Mahalanobis distance;Maximum trimmed likelihood estimator;Minimum covariance determinant estimator;Mixed data;Multiple outliers;Robust diagnostics | |
| dc.title (題名) | Maximum trimmed likelihood estimator for multivariate mixed continuous and categorical data | |
| dc.type (資料類型) | article | en |
| dc.identifier.doi (DOI) | 10.1016/j.csda.2007.06.026 | |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1016/j.csda.2007.06.026 | |
