IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v104y2015icp7-13.html
   My bibliography  Save this article

Multivariate EWMA control chart based on a variable selection using AIC for multivariate statistical process monitoring

Author

Listed:
  • Nishimura, Kazuya
  • Matsuura, Shun
  • Suzuki, Hideo

Abstract

In multivariate statistical process control, when a process shift occurs, not all variables but a few variables may shift from the in-control state. This paper proposes a multivariate EWMA control chart based on a variable selection using AIC.

Suggested Citation

  • Nishimura, Kazuya & Matsuura, Shun & Suzuki, Hideo, 2015. "Multivariate EWMA control chart based on a variable selection using AIC for multivariate statistical process monitoring," Statistics & Probability Letters, Elsevier, vol. 104(C), pages 7-13.
    • Handle: RePEc:eee:stapro:v:104:y:2015:i:c:p:7-13
    DOI: 10.1016/j.spl.2015.05.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715215001522
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2015.05.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Bo Li & Kaibo Wang & Arthur Yeh, 2013. "Monitoring the covariance matrix via penalized likelihood estimation," IISE Transactions, Taylor & Francis Journals, vol. 45(2), pages 132-146.
    2. Zou, Changliang & Qiu, Peihua, 2009. "Multivariate Statistical Process Control Using LASSO," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1586-1596.
    3. Wang, Kaibo & Yeh, Arthur B. & Li, Bo, 2014. "Simultaneous monitoring of process mean vector and covariance matrix via penalized likelihood estimation," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 206-217.
    4. Bersimis, Sotiris & Psarakis, Stelios & Panaretos, John, 2006. "Multivariate Statistical Process Control Charts: An Overview," MPRA Paper 6399, University Library of Munich, Germany.
    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. Taghikhah, Firouzeh Rosa & Taghikhah, Masoud & Marshall, Jonathan Paul & Voinov, Alexey, 2024. "Navigating the community renewable energy landscape: An analytics-driven policy formulation," Applied Energy, Elsevier, vol. 362(C).

    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. Sangahn Kim & Mehmet Turkoz & Myong K. Jeong & Elsayed A. Elsayed, 2024. "Monitoring of group-structured high-dimensional processes via sparse group LASSO," Annals of Operations Research, Springer, vol. 340(2), pages 891-911, September.
    2. Molly C. Klanderman & Kathryn B. Newhart & Tzahi Y. Cath & Amanda S. Hering, 2020. "Fault isolation for a complex decentralized waste water treatment facility," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 931-951, August.
    3. Wang, Kaibo & Yeh, Arthur B. & Li, Bo, 2014. "Simultaneous monitoring of process mean vector and covariance matrix via penalized likelihood estimation," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 206-217.
    4. Ahmad, M. Rauf & Ahmed, S. Ejaz, 2021. "On the distribution of the T2 statistic, used in statistical process monitoring, for high-dimensional data," Statistics & Probability Letters, Elsevier, vol. 168(C).
    5. Linus Schiöler & Marianne Fris�n, 2012. "Multivariate outbreak detection," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 223-242, April.
    6. Wen-An Yang, 2016. "Simultaneous monitoring of mean vector and covariance matrix shifts in bivariate manufacturing processes using hybrid ensemble learning-based model," Journal of Intelligent Manufacturing, Springer, vol. 27(4), pages 845-874, August.
    7. Marianne Frisen & Eva Andersson & Linus Schioler, 2010. "Evaluation of multivariate surveillance," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(12), pages 2089-2100.
    8. Frisén, Marianne & Andersson, Eva & Schiöler, Linus, 2009. "Sufficient reduction in multivariate surveillance," Research Reports 2009:2, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    9. Bei Wang & Xuefeng Yan, 2019. "Real-time monitoring of chemical processes based on variation information of principal component analysis model," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 795-808, February.
    10. Sotirios Bersimis & Stavros Degiannakis & Dimitrios Georgakellos, 2017. "Real-time monitoring of carbon monoxide using value-at-risk measure and control charting," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(1), pages 89-108, January.
    11. Sotiris Bersimis & Kostas Triantafyllopoulos, 2020. "Dynamic Non-parametric Monitoring of Air-Pollution," Methodology and Computing in Applied Probability, Springer, vol. 22(4), pages 1457-1479, December.
    12. Jinho Kim & Myong K. Jeong & Elsayed A. Elsayed, 2017. "Monitoring multistage processes with autocorrelated observations," International Journal of Production Research, Taylor & Francis Journals, vol. 55(8), pages 2385-2396, April.
    13. Marianne Frisén, 2014. "Spatial outbreak detection based on inference principles for multivariate surveillance," IISE Transactions, Taylor & Francis Journals, vol. 46(8), pages 759-769, August.
    14. Amir Ahmadi-Javid & Mohsen Ebadi, 2021. "Economic design of memory-type control charts: The fallacy of the formula proposed by Lorenzen and Vance (1986)," Computational Statistics, Springer, vol. 36(1), pages 661-690, March.
    15. Frisén, Marianne, 2011. "Methods and evaluations for surveillance in industry, business, finance, and public health," Research Reports 2011:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    16. Dong Ding & Fugee Tsung & Jian Li, 2016. "Directional control schemes for processes with mixed-type data," International Journal of Production Research, Taylor & Francis Journals, vol. 54(6), pages 1594-1609, March.
    17. Dariush Najarzadeh, 2019. "Testing equality of standardized generalized variances of k multivariate normal populations with arbitrary dimensions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 593-623, December.
    18. Vanajah Siva, 2012. "Improvement in Product Development: Use of back-end data to support upstream efforts of Robust Design Methodology," Quality Innovation Prosperity, Technical University of Košice, Department of integrated management, vol. 16(2).
    19. Aven, Terje, 2014. "On the meaning of the special-cause variation concept used in the quality discourse – And its link to unforeseen and surprising events in risk management," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 81-86.
    20. Lianjie Shu & Jinyu Fan, 2018. "A distribution‐free control chart for monitoring high‐dimensional processes based on interpoint distances," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(4), pages 317-330, June.

    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:stapro:v:104:y:2015:i:c:p:7-13. 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/wps/find/journaldescription.cws_home/622892/description#description .

    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.