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https://ah.lib.nccu.edu.tw/handle/140.119/71323
題名: | Nonparametric Profile Monitoring in Multi-dimensional Data Spaces. | 作者: | Hung,Ying-Chao;Tsai,Wen-Chi;Yang,Su-Fen;Chuang,Shih-Chung;Tseng,Yi-Kuan | 貢獻者: | 統計系 | 關鍵詞: | Nonparametric profile monitoring; Support Vector Regression; Block bootstrap; Confidence region | 日期: | Feb-2012 | 上傳時間: | 11-Nov-2014 | 摘要: | Profile monitoring has received increasingly attention in a wide range of applications in statistical process control (SPC). In this work, we propose a framework for monitoring nonparametric profiles in multi-dimensional data spaces. The framework has the following important features: (i) a flexible and computationally efficient smoothing technique, called Support Vector Regression, is employed to describe the relationship between the response variable and the explanatory variables; (ii) the usual structural assumptions on the residuals are not required; and (iii) the dependence structure for the within-profile observations is appropriately accommodated. Finally, real AIDS data collected from hospitals in Taiwan are used to illustrate and evaluate our proposed framework. | 關聯: | Journal of Process Control,22(2),397-403 | 資料類型: | article | DOI: | http://dx.doi.org/http://dx.doi.org/10.1016/j.jprocont.2011.12.009 |
Appears in Collections: | 期刊論文 |
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