臺灣博碩士論文加值系統

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.

1.Introduction 1
2.Empirical Bayes inference 3
3.Empirical Bayes process monitoring scheme 10
3.1 Known a 12
3.2 Unknown a 15
4.Simulation study 19
5.Conclusions and possible generalizations 23
Appendix A 23
Appendix B 24
Appendix C 26
References 27

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