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| 題名 | A Framework for Nonparametric Profile Monitoring. online publish |
| 作者 | 楊素芬;洪英超 Chuang, Shih-Chung ;Hung, Ying-Chao ;Tsai, Wen-Chi ;Yang, Su-Fen |
| 貢獻者 | 統計系 |
| 關鍵詞 | Nonparametric profile monitoring; B-spline; Block bootstrap; Confidence band; Curve depth |
| 日期 | 2012.12 |
| 上傳時間 | 11-十一月-2013 17:46:31 (UTC+8) |
| 摘要 | Control charts have been widely used for monitoring the functional relationship between a response variable and some explanatory variable(s) (called profile) in various industrial applications. In this article, we propose an easy-to-implement framework for monitoring nonparametric profiles in both Phase I and Phase II of a control chart scheme. The proposed framework includes the following steps: (i) data cleaning; (ii) fitting B-spline models; (iii) resampling for dependent data using block bootstrap method; (iv) constructing the confidence band based on bootstrap curve depths; and (v) monitoring profiles online based on curve matching. It should be noted that, the proposed method does not require any structural assumptions on the data and, it can appropriately accommodate the dependence structure of the within-profile observations. We illustrate and evaluate our proposed framework by using a real data set. |
| 關聯 | Computers and Industrial Engineering, 64(1), 482-491 |
| 資料類型 | article |
| DOI | http://dx.doi.org/http://dx.doi.org/10.1016/j.cie.2012.08.006 |
| dc.contributor | 統計系 | en_US |
| dc.creator (作者) | 楊素芬;洪英超 | zh_TW |
| dc.creator (作者) | Chuang, Shih-Chung ;Hung, Ying-Chao ;Tsai, Wen-Chi ;Yang, Su-Fen | - |
| dc.date (日期) | 2012.12 | en_US |
| dc.date.accessioned | 11-十一月-2013 17:46:31 (UTC+8) | - |
| dc.date.available | 11-十一月-2013 17:46:31 (UTC+8) | - |
| dc.date.issued (上傳時間) | 11-十一月-2013 17:46:31 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/61609 | - |
| dc.description.abstract (摘要) | Control charts have been widely used for monitoring the functional relationship between a response variable and some explanatory variable(s) (called profile) in various industrial applications. In this article, we propose an easy-to-implement framework for monitoring nonparametric profiles in both Phase I and Phase II of a control chart scheme. The proposed framework includes the following steps: (i) data cleaning; (ii) fitting B-spline models; (iii) resampling for dependent data using block bootstrap method; (iv) constructing the confidence band based on bootstrap curve depths; and (v) monitoring profiles online based on curve matching. It should be noted that, the proposed method does not require any structural assumptions on the data and, it can appropriately accommodate the dependence structure of the within-profile observations. We illustrate and evaluate our proposed framework by using a real data set. | en_US |
| dc.format.extent | 486153 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.language.iso | en_US | - |
| dc.relation (關聯) | Computers and Industrial Engineering, 64(1), 482-491 | en_US |
| dc.subject (關鍵詞) | Nonparametric profile monitoring; B-spline; Block bootstrap; Confidence band; Curve depth | en_US |
| dc.title (題名) | A Framework for Nonparametric Profile Monitoring. online publish | en_US |
| dc.type (資料類型) | article | en |
| dc.identifier.doi (DOI) | 10.1016/j.cie.2012.08.006 | en_US |
| dc.doi.uri (DOI) | http://dx.doi.org/http://dx.doi.org/10.1016/j.cie.2012.08.006 | en_US |