Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 廖小慧 | en_US |
dc.contributor.author | Hsiao-Hui Liao | en_US |
dc.contributor.author | 陳志榮 | en_US |
dc.contributor.author | 洪志真 | en_US |
dc.contributor.author | Chih-Rung Chen | en_US |
dc.contributor.author | Jyh-Jen H. Shiau | en_US |
dc.date.accessioned | 2014-12-12T02:30:08Z | - |
dc.date.available | 2014-12-12T02:30:08Z | - |
dc.date.issued | 2002 | en_US |
dc.identifier.uri | http://140.113.39.130/cdrfb3/record/nctu/#NT910337011 | en_US |
dc.identifier.uri | http://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.abstract | The 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.iso | en_US | en_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.subject | Empirical Bayes | en_US |
dc.subject | Categorical data | en_US |
dc.subject | Likelihood inference | en_US |
dc.subject | Likelihood Ratio test | en_US |
dc.subject | Control chart | en_US |
dc.subject | Quality control | en_US |
dc.title | 類別資料的經驗貝氏製程監控技術 | zh_TW |
dc.title | Empirical Bayes process monitoring techniques for categorical data | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | 統計學研究所 | zh_TW |
Appears in Collections: | Thesis |