IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v53y2009i4p1440-1448.html
   My bibliography  Save this article

Control chart based on likelihood ratio for monitoring linear profiles

Author

Listed:
  • Zhang, Jiujun
  • Li, Zhonghua
  • Wang, Zhaojun

Abstract

A control chart based on the likelihood ratio is proposed for monitoring the linear profiles. The new chart which integrates the EWMA procedure can detect shifts in either the intercept or the slope or the standard deviation, or simultaneously by a single chart which is different from other control charts in literature for linear profiles. The results by Monte Carlo simulation show that our approach has good performance across a wide range of possible shifts. We show that the new method has competitive performance relative to other methods in literature in terms of ARL, and another feature of the new chart is that it can be easily designed. The application of our proposed method is illustrated by a real data example from an optical imaging system.

Suggested Citation

  • Zhang, Jiujun & Li, Zhonghua & Wang, Zhaojun, 2009. "Control chart based on likelihood ratio for monitoring linear profiles," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1440-1448, February.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:4:p:1440-1448
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(08)00574-4
    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.

    Citations

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


    Cited by:

    1. Zhou, Qin & Luo, Yunzhao & Wang, Zhaojun, 2010. "A control chart based on likelihood ratio test for detecting patterned mean and variance shifts," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1634-1645, June.
    2. Wenhui Liu & Zhonghua Li & Zhaojun Wang, 2022. "Monitoring of Linear Profiles Using Linear Mixed Model in the Presence of Measurement Errors," Mathematics, MDPI, vol. 10(24), pages 1-17, December.
    3. Ho Linda Lee & El Said Mahmoud & Kim Ricardo Wonseuk, 2010. "Monitoring the Parameters of the Market Model by Linear Profile Procedures," Stochastics and Quality Control, De Gruyter, vol. 25(1), pages 81-96, January.
    4. Shahram Ghobadi & Kazem Noghondarian & Rassoul Noorossana & S. Mirhosseini, 2014. "Developing a multivariate approach to monitor fuzzy quality profiles," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(2), pages 817-836, March.

    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:4:p:1440-1448. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.