IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v53y2009i12p4210-4220.html
   My bibliography  Save this article

Comparison of p control charts for low defective rate

Author

Listed:
  • Wang, Hsiuying

Abstract

It is well known that the conventional p control chart constructed by the normal approximation for the binomial distribution suffers a serious inaccuracy in the monitor process when the true rate of nonconforming items is small. A similar problem also arises in the binomial confidence interval estimation. Adjusted confidence intervals are established in the literature to improve the coverage probability when the binomial proportion is small. In this paper, a new p control chart based on an adjusted confidence interval is established, which can substantially improve the existing control charts when the nonconforming rate is small.

Suggested Citation

  • Wang, Hsiuying, 2009. "Comparison of p control charts for low defective rate," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4210-4220, October.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:12:p:4210-4220
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(09)00199-6
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Hsiuying, 2008. "Coverage probability of prediction intervals for discrete random variables," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 17-26, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Emura, Takeshi & Lai, Ching-Chieh & Sun, Li-Hsien, 2023. "Change point estimation under a copula-based Markov chain model for binomial time series," Econometrics and Statistics, Elsevier, vol. 28(C), pages 120-137.
    2. Nasrullah Khan & Muhammad Aslam & Kyung-Jun Kim & Chi-Hyuck Jun, 2017. "A mixed control chart adapted to the truncated life test based on the Weibull distribution," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(1), pages 43-55.
    3. Bersimis, Sotiris & Koutras, Markos V. & Maravelakis, Petros E., 2014. "A compound control chart for monitoring and controlling high quality processes," European Journal of Operational Research, Elsevier, vol. 233(3), pages 595-603.
    4. Emura, Takeshi & Lin, Yi-Shuan, 2013. "A comparison of normal approximation rules for attribute control charts," MPRA Paper 51029, University Library of Munich, Germany.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. K. Krishnamoorthy & Shanshan Lv, 2018. "Highest posterior mass prediction intervals for binomial and poisson distributions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(7), pages 775-796, October.
    2. Qinglong Tian & Daniel J. Nordman & William Q. Meeker, 2022. "Constructing Prediction Intervals Using the Likelihood Ratio Statistic," INFORMS Joural on Data Science, INFORMS, vol. 1(1), pages 63-80, April.
    3. N. Balakrishnan & E. Beutner & E. Cramer, 2013. "Computational aspects of statistical intervals based on two Type-II censored samples," Computational Statistics, Springer, vol. 28(3), pages 893-917, June.
    4. Annika Homburg & Christian H. Weiß & Layth C. Alwan & Gabriel Frahm & Rainer Göb, 2021. "A performance analysis of prediction intervals for count time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 603-625, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:53:y:2009:i:12:p:4210-4220. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.