English  |  正體中文  |  简体中文  |  Items with full text/Total items : 52568/87720 (60%)
Visitors : 9374581      Online Users : 162
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/106159

    Title: Conditional maximum likelihood estimation for control charts in the presence of correlation
    Authors: Tsai, T.-R.;Chiang, Y.-C.;Wu, S.-J.
    Keywords: Autoregressive moving average model;exponentially weighted moving average control charts;first-order autoregressive model;maximum likelihood estimation;Shewhart control chart
    Date: 2004/12/01
    Issue Date: 2016-04-22 13:22:26 (UTC+8)
    Abstract: In practice, the observations are usually autocorrelated. The
    autocorrelation between successive observations has a large impact on control
    charts with the assumption of independence. It can decrease the in-control
    average run length which leads to a higher false alarm rate than in the case
    of independent process. This paper considers the problem of monitoring the
    mean of AR(1) process with a random error and provides a conditional maximum
    likelihood estimation method to improve the control chart performance
    when the sample size is small. Numerical result shows that the standard estimation
    method is very unstable when the sample size is small, and there is
    a large probability that the standard estimation method breaks down if the
    level of correlation between successive means is small-to-moderate. The new
    method given here overcomes this difficulty.
    Relation: Brazilian Journal of Probability and Statistics 18(2), pp.151-162
    Appears in Collections:[統計學系暨研究所] 期刊論文

    Files in This Item:

    File Description SizeFormat

    All items in 機構典藏 are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback