完整後設資料紀錄
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dc.contributor.author邱湘雲en_US
dc.contributor.authorHsiang Yun Chiuen_US
dc.contributor.author洪志真en_US
dc.contributor.authorJyh-Jen Horng Shiauen_US
dc.date.accessioned2014-12-12T02:24:55Z-
dc.date.available2014-12-12T02:24:55Z-
dc.date.issued2000en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#NT890337003en_US
dc.identifier.urihttp://hdl.handle.net/11536/66753-
dc.description.abstract近幾年,統計製程管制的另一個重要焦點在於發展監控具有自我相關性的資料的控制圖。 本篇文章中, 我們研究多變量自我相關性資料的控制圖。 將介紹多變量特殊原因管制圖及推導其連串長度分配。 我們並且針對VAR(1) 的製程, 將多變量特殊原因管制圖與Kramer和Schmid (1997) 所提的時間數列資料的MEWMA 控制圖和將殘差值應用在Lowry 等人所提的多變量EWMA 管制圖做ARL值的比較。 最後將方法應用在兩個實際例子上 。zh_TW
dc.description.abstractIn recent years, an important focus of research in statistical process control (SPC) is control charts for autocorrelated data. In this paper, a multivariate special-cause chart (MSCC) is introduced. The run length distributions of the multivariate special-cause chart are derived for ARMA process. We also compare this chart on the basis of the average run length (ARL) with the MEWMA control chart for time series (Kramer and Schmid, 1997) and the MEWMA control chart applied to residuals for VAR (1) processes. Finally, MSCC is demonstrated with two real examples.en_US
dc.language.isoen_USen_US
dc.subject控制圖zh_TW
dc.subject連串長度分配zh_TW
dc.subjectcontrol charten_US
dc.subjectrun length distributionen_US
dc.title多變量自我相關性資料的製程監控zh_TW
dc.titleProcess Monitoring for Multivariate Autocorrelated Dataen_US
dc.typeThesisen_US
dc.contributor.department統計學研究所zh_TW
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