標題: 利用概似比方法之類別資料的經驗貝氏製程監控技術
An Empirical Bayes Process Monitoring Technique for Categorical Data Utilizing the Likelihood Ratio Method
作者: 林姿吟
Tzu-Yin Lin
陳志榮
洪志真
Chih-Rung Chen
Jyh-Jen H. Shiau
統計學研究所
關鍵字: Empirical Bayes;Process monitoring;Categorical data;Normal-binomial;Normal-multinomial;Likelihood ratio;Control chart;Quality control;經驗貝式;製程監控;類別資料;常態-二項式;常態-多項式;概似比;管制圖;品質管制
公開日期: 2003
摘要: 本篇論文的目的是對於製程中的類別資料利用概似比的方法發展一個經驗貝氏。假設常態二項式或多項式模型,我們首先探討對於製程中的類別資料之經驗貝式的推論方法。然後我們提出一個對於製程中的類別資料利用概似比的方法之經驗貝式製程監控技術,最後我們研究此技術之製程平均長度。
The purpose of the paper is to develop an empirical Bayes process monitoring technique for manufacturing categorical data utilizing the likelihood ratio method. First, assuming the normal-binomial or -multinomial model, an empirical Bayes inference for manufacturing categorical data is discussed. Next, utilizing the likelihood ratio method, an empirical Bayes process monitoring technique for manufacturing categorical data is proposed. Finally, the average run length behavior of the proposed process monitoring scheme is investigated.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT009126514
http://hdl.handle.net/11536/55501
Appears in Collections:Thesis


Files in This Item:

  1. 651401.pdf
  2. 651402.pdf

If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.