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dc.contributor.author廖小慧en_US
dc.contributor.authorHsiao-Hui Liaoen_US
dc.contributor.author陳志榮en_US
dc.contributor.author洪志真en_US
dc.contributor.authorChih-Rung Chenen_US
dc.contributor.authorJyh-Jen H. Shiauen_US
dc.date.accessioned2014-12-12T02:30:08Z-
dc.date.available2014-12-12T02:30:08Z-
dc.date.issued2002en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#NT910337011en_US
dc.identifier.urihttp://hdl.handle.net/11536/70039-
dc.description.abstract本篇論文的目的是發展有母數與半母數的經驗貝氏方法,用來監控製造過程中的類別資料。首先,先回顧有母數與半母數的經驗貝氏推論。其次,提出製造過程中可以用來監控類別資料的有母數與半母數的經驗貝氏方法。最後,將所提出的方法藉由模擬的技巧與2003年蕭和其他人的論文作比較。zh_TW
dc.description.abstractThe purpose of this paper is to develop both parametric and semipararmetric empirical Bayes methods to monitor categorical data in manufacturing processes. Both parametric and semiparametric empirical Bayes inferences are first reviewed. Next, both parametric and semiparametric empirical Bayes methods to monitor categorical data in manufacturing processes are proposed. Finally, both proposed methods are compared with that in Shaiu et al.\ (2003) through simulations.en_US
dc.language.isoen_USen_US
dc.subject經驗貝氏zh_TW
dc.subject類別資料zh_TW
dc.subject概似推論zh_TW
dc.subject概似比檢定zh_TW
dc.subject管制圖zh_TW
dc.subject品質管制zh_TW
dc.subjectEmpirical Bayesen_US
dc.subjectCategorical dataen_US
dc.subjectLikelihood inferenceen_US
dc.subjectLikelihood Ratio testen_US
dc.subjectControl charten_US
dc.subjectQuality controlen_US
dc.title類別資料的經驗貝氏製程監控技術zh_TW
dc.titleEmpirical Bayes process monitoring techniques for categorical dataen_US
dc.typeThesisen_US
dc.contributor.department統計學研究所zh_TW
Appears in Collections:Thesis