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    請使用永久網址來引用或連結此文件: https://ir.lib.ncu.edu.tw/handle/987654321/105675


    題名: A decision theoretic approach to change point estimation for binomial CUSUM control charts
    作者: 江村剛志;Emura, Takeshi;Ho, Yi-Ting
    貢獻者: 理學院統計研究所
    關鍵詞: 62L0;Attribute control chart;Binomials;Confidence intervals;Control charts;Decision theory;Economic models;Estimators;Jewelry;Maximum likelihood estimators;np-chart;parametric bootstrap;Sequential analysis;SPRT;Statistical process control
    日期: 2016-04-02
    上傳時間: 2026-04-23 12:47:05 (UTC+8)
    出版者: Taylor and Francis Ltd.;Philadelphia: Taylor & Francis
    摘要: 摘要: Detecting when the process has changed is a classical problem in sequential analysis and is an important practical issue in statistical process control. This article is concerned about the binomial cumulative sum (CUSUM) control chart, which is extensively applied to industrial process control, health care, public health surveillance, and other fields. For the binomial CUSUM, a maximum likelihood estimator has been proposed to estimate the change point. In our article, following a decision theoretic approach, we develop a new estimator that aims to improve the existing methods. For interval estimation, we propose a parametric bootstrap procedure to construct the confidence set of the change point. We compare our proposed method with the maximum likelihood estimator and Page's last zero estimator in terms of mean squared error by simulations. We find that the proposed method gives more unbiased and robust results than the existing procedures under various parameter designs. We analyze jewelry manufacturing data for illustration.
    出版者: Philadelphia: Taylor & Francis
    出版日期: 2016-04-02
    出處: Sequential Analysis, 2016-04, Vol.35 (2), p.238-253
    版權: Copyright © Taylor & Francis Group, LLC 2016
    版權: Copyright © Taylor & Francis Group, LLC
    識別號: ISSN: 0747-4946
    識別號: EISSN: 1532-4176
    識別號: DOI: 10.1080/07474946.2016.1165543
    顯示於類別:[統計研究所] 期刊論文

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