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題名 具相關誤差之線性迴歸模型的剖面曲線監測
其他題名 Monitoring Profile Based on a Linear Regression Model with Correlated Errors
作者 鄭宗記
貢獻者 國立政治大學統計學系
行政院國家科學委員會
關鍵詞 誤差相關;Hotelling‘s T2 統計量;統計製程管制。
日期 2011
上傳時間 30-八月-2012 09:59:25 (UTC+8)
摘要 Profile monitoring is a relatively new technique and becoming popular in the area of quality control, as it is used when the process is characterized by a profile at each time period. This project considers the situation where profiles are modeled parametrically using a multiple linear regression model with random errors following an autoregressive moving-average process. Diagnostic schemes to find out-of-control samples are developed for this purpose. A simulation study examines the performance of the proposed approach based on average run length criterion. A real data example is implemented to illustrate the results, in which both phase I and phase II schemes are considered.
剖面曲線監測(profile monitoring)在品質管制的領域中,是一相對新且漸為受到重視的方法;其應用於在給定的時間內,以一剖面曲線(profile)描繪該一製程。本研究計畫主要討論的剖面曲線為誤差具自我相關移動平均過程(autoregressive moving-average process)的複迴歸模型,將提出相關統計方法在此類剖面曲線的製程下,藉以發現失控樣本的診斷設計。研究以電腦模擬方式檢驗所提出的方法;同時,藉由一個實際的資料分析陳示此方法。
關聯 基礎研究
學術補助
研究期間:10008~ 10107
研究經費:356仟元
資料類型 report
dc.contributor 國立政治大學統計學系en_US
dc.contributor 行政院國家科學委員會en_US
dc.creator (作者) 鄭宗記zh_TW
dc.date (日期) 2011en_US
dc.date.accessioned 30-八月-2012 09:59:25 (UTC+8)-
dc.date.available 30-八月-2012 09:59:25 (UTC+8)-
dc.date.issued (上傳時間) 30-八月-2012 09:59:25 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/53406-
dc.description.abstract (摘要) Profile monitoring is a relatively new technique and becoming popular in the area of quality control, as it is used when the process is characterized by a profile at each time period. This project considers the situation where profiles are modeled parametrically using a multiple linear regression model with random errors following an autoregressive moving-average process. Diagnostic schemes to find out-of-control samples are developed for this purpose. A simulation study examines the performance of the proposed approach based on average run length criterion. A real data example is implemented to illustrate the results, in which both phase I and phase II schemes are considered.en_US
dc.description.abstract (摘要) 剖面曲線監測(profile monitoring)在品質管制的領域中,是一相對新且漸為受到重視的方法;其應用於在給定的時間內,以一剖面曲線(profile)描繪該一製程。本研究計畫主要討論的剖面曲線為誤差具自我相關移動平均過程(autoregressive moving-average process)的複迴歸模型,將提出相關統計方法在此類剖面曲線的製程下,藉以發現失控樣本的診斷設計。研究以電腦模擬方式檢驗所提出的方法;同時,藉由一個實際的資料分析陳示此方法。-
dc.language.iso en_US-
dc.relation (關聯) 基礎研究en_US
dc.relation (關聯) 學術補助en_US
dc.relation (關聯) 研究期間:10008~ 10107en_US
dc.relation (關聯) 研究經費:356仟元en_US
dc.subject (關鍵詞) 誤差相關;Hotelling‘s T2 統計量;統計製程管制。en_US
dc.title (題名) 具相關誤差之線性迴歸模型的剖面曲線監測zh_TW
dc.title.alternative (其他題名) Monitoring Profile Based on a Linear Regression Model with Correlated Errorsen_US
dc.type (資料類型) reporten