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Sequential rank CUSUM charts for angular data

Author

Listed:
  • Lombard, F.
  • Hawkins, Douglas M.
  • Potgieter, Cornelis J.

Abstract

A cumulative sum (CUSUM) control chart has desirable properties for checking whether a distribution has changed from an in-control to an out-of-control setting. Distribution-free CUSUMs based on sequential ranks to detect changes in the mean direction and dispersion of angular data are developed and some of their properties are illustrated by theoretical calculations and Monte Carlo simulation. Three applications to sequentially observed angular data from health science, industrial quality control and astrophysics are discussed.

Suggested Citation

  • Lombard, F. & Hawkins, Douglas M. & Potgieter, Cornelis J., 2017. "Sequential rank CUSUM charts for angular data," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 268-279.
    • Handle: RePEc:eee:csdana:v:105:y:2017:i:c:p:268-279
    DOI: 10.1016/j.csda.2016.08.001
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    References listed on IDEAS

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    1. David McDonald, 1990. "A cusum procedure based on sequential ranks," Naval Research Logistics (NRL), John Wiley & Sons, vol. 37(5), pages 627-646, October.
    2. Berens, Philipp, 2009. "CircStat: A MATLAB Toolbox for Circular Statistics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 31(i10).
    3. F. Lombard & R. K. Maxwell, 2012. "A cusum procedure to detect deviations from uniformity in angular data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 1871-1880, April.
    4. Taylor, Charles C., 2008. "Automatic bandwidth selection for circular density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3493-3500, March.
    5. Douglas M. Hawkins & F. Lombard, 2015. "Segmentation of circular data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(1), pages 88-97, January.
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    Cited by:

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