Nonparametric adaptive CUSUM chart for detecting arbitrary distributional changes

Jun Li
Nonparametric control charts that can detect arbitrary distributional changes are highly desirable due to their flexibility to adapt to different distributional assumptions and changes. However, most of the nonparametric control charts in the literature either can only detect location changes, or involve intensive computation. In this article, we propose a new nonparametric adaptive CUSUM chart. The proposed control chart can detect arbitrary distributional changes and is computationally efficient. Its self-starting nature makes the proposed control...
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