Control charts based on randomized quantile residuals

Kayoung Park, Dongmin Jung, Jong Min Kim

    Research output: Contribution to journalArticlepeer-review

    4 Scopus citations

    Abstract

    In practice, quality characteristics do not always follow a normal distribution, and quality control processes sometimes generate non-normal response outcomes, including continuous non-normal data and discrete count data. Thus, achieving better results in such situations requires a new control chart derived from various types of response variables. This study proposes a procedure for monitoring response variables that uses control charts based on randomized quantile residuals obtained from a fitted regression model. Simulation studies demonstrate the performance of the proposed control charts under various situations. We illustrate the procedure using two real-data examples, based on normal and negative binomial regression models, respectively. The simulation and real-data results support our proposed procedure.

    Original languageEnglish (US)
    Pages (from-to)716-729
    Number of pages14
    JournalApplied Stochastic Models in Business and Industry
    Volume36
    Issue number4
    DOIs
    StatePublished - Jul 1 2020

    Bibliographical note

    Publisher Copyright:
    © 2020 John Wiley & Sons, Ltd.

    Copyright:
    Copyright 2020 Elsevier B.V., All rights reserved.

    Keywords

    • control chart
    • deviance residual
    • randomized quantile residual
    • statistical processes control

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