Parametric control charts

Willem/Wim Albers, W.C.M. Kallenberg, S. Nurdiati

    Research output: Book/ReportReportProfessional

    44 Downloads (Pure)

    Abstract

    Standard control charts are based on the assumption that the observations are normally distributed. In practice, normality often fails and consequently the false alarm rate is seriously in error. Application of a nonparametric approach is only possible with many Phase I observations. Since nowadays such very large sample sizes are usually not available, there is need for an intermediate approach by considering a larger parametric model containing the normal family as a submodel. In this paper control limits are presented in such larger parametric models, with emphasis on the so called normal power family. Correction terms are derived, taking into account that the parameters are estimated. Simulation results show that the control limits are accurate, not only in the considered parametric family, but also for common distributions outside the parametric family, thus covering a broad class of distributions.
    Original languageUndefined
    Place of PublicationEnschede
    PublisherUniversity of Twente, Department of Applied Mathematics
    Number of pages32
    Publication statusPublished - 2002

    Publication series

    NameMemorandum Faculty of Mathematical Sciences
    PublisherUniversity of Twente, Faculty of Mathematical Sciences
    No.1623
    ISSN (Print)0169-2690

    Keywords

    • MSC-62P30
    • MSC-65C05
    • METIS-206702
    • IR-65810
    • EWI-3443
    • MSC-62F12

    Cite this

    Albers, WW., Kallenberg, W. C. M., & Nurdiati, S. (2002). Parametric control charts. (Memorandum Faculty of Mathematical Sciences; No. 1623). Enschede: University of Twente, Department of Applied Mathematics.
    Albers, Willem/Wim ; Kallenberg, W.C.M. ; Nurdiati, S. / Parametric control charts. Enschede : University of Twente, Department of Applied Mathematics, 2002. 32 p. (Memorandum Faculty of Mathematical Sciences; 1623).
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    title = "Parametric control charts",
    abstract = "Standard control charts are based on the assumption that the observations are normally distributed. In practice, normality often fails and consequently the false alarm rate is seriously in error. Application of a nonparametric approach is only possible with many Phase I observations. Since nowadays such very large sample sizes are usually not available, there is need for an intermediate approach by considering a larger parametric model containing the normal family as a submodel. In this paper control limits are presented in such larger parametric models, with emphasis on the so called normal power family. Correction terms are derived, taking into account that the parameters are estimated. Simulation results show that the control limits are accurate, not only in the considered parametric family, but also for common distributions outside the parametric family, thus covering a broad class of distributions.",
    keywords = "MSC-62P30, MSC-65C05, METIS-206702, IR-65810, EWI-3443, MSC-62F12",
    author = "Willem/Wim Albers and W.C.M. Kallenberg and S. Nurdiati",
    note = "Imported from MEMORANDA",
    year = "2002",
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    series = "Memorandum Faculty of Mathematical Sciences",
    publisher = "University of Twente, Department of Applied Mathematics",
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    }

    Albers, WW, Kallenberg, WCM & Nurdiati, S 2002, Parametric control charts. Memorandum Faculty of Mathematical Sciences, no. 1623, University of Twente, Department of Applied Mathematics, Enschede.

    Parametric control charts. / Albers, Willem/Wim; Kallenberg, W.C.M.; Nurdiati, S.

    Enschede : University of Twente, Department of Applied Mathematics, 2002. 32 p. (Memorandum Faculty of Mathematical Sciences; No. 1623).

    Research output: Book/ReportReportProfessional

    TY - BOOK

    T1 - Parametric control charts

    AU - Albers, Willem/Wim

    AU - Kallenberg, W.C.M.

    AU - Nurdiati, S.

    N1 - Imported from MEMORANDA

    PY - 2002

    Y1 - 2002

    N2 - Standard control charts are based on the assumption that the observations are normally distributed. In practice, normality often fails and consequently the false alarm rate is seriously in error. Application of a nonparametric approach is only possible with many Phase I observations. Since nowadays such very large sample sizes are usually not available, there is need for an intermediate approach by considering a larger parametric model containing the normal family as a submodel. In this paper control limits are presented in such larger parametric models, with emphasis on the so called normal power family. Correction terms are derived, taking into account that the parameters are estimated. Simulation results show that the control limits are accurate, not only in the considered parametric family, but also for common distributions outside the parametric family, thus covering a broad class of distributions.

    AB - Standard control charts are based on the assumption that the observations are normally distributed. In practice, normality often fails and consequently the false alarm rate is seriously in error. Application of a nonparametric approach is only possible with many Phase I observations. Since nowadays such very large sample sizes are usually not available, there is need for an intermediate approach by considering a larger parametric model containing the normal family as a submodel. In this paper control limits are presented in such larger parametric models, with emphasis on the so called normal power family. Correction terms are derived, taking into account that the parameters are estimated. Simulation results show that the control limits are accurate, not only in the considered parametric family, but also for common distributions outside the parametric family, thus covering a broad class of distributions.

    KW - MSC-62P30

    KW - MSC-65C05

    KW - METIS-206702

    KW - IR-65810

    KW - EWI-3443

    KW - MSC-62F12

    M3 - Report

    T3 - Memorandum Faculty of Mathematical Sciences

    BT - Parametric control charts

    PB - University of Twente, Department of Applied Mathematics

    CY - Enschede

    ER -

    Albers WW, Kallenberg WCM, Nurdiati S. Parametric control charts. Enschede: University of Twente, Department of Applied Mathematics, 2002. 32 p. (Memorandum Faculty of Mathematical Sciences; 1623).