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Nonparametric permutation-based control charts for ordinal data. (English) Zbl 1383.62343
Akritas, Michael G. (ed.) et al., Topics in nonparametric statistics. Proceedings of the first conference of the International Society for Nonparametric Statistics, ISNPS, Chalkidiki, Greece, June 15–19, 2012. New York, NY: Springer (ISBN 978-1-4939-0568-3/hbk; 978-1-4939-0569-0/ebook). Springer Proceedings in Mathematics & Statistics 74, 309-321 (2014).
Summary: In the literature of statistical process control (SPC), design and implementation of traditional Shewart-based control charts requires the assumption that the process response distribution follows a parametric form (e.g., normal). However, since in practice, ordinal observations may not follow the pre-specified parametric distribution these charts may not be reliable. In this connection, this work aims at providing a contribution to the nonparametric SPC literature, proposing univariate and multivariate nonparametric permutation-based control charts for ordinal response variables which are not only interesting as methodological solution but they have a very practical value particularly within the context of monitoring some measure of user’s satisfaction, loyalty, etc. related to use of a given service. As confirmed by the simulation study and by the application to a real case study in the field of monitoring of customer satisfaction in services, we can state that the proposed NPC chart for ordered categorical response variables is certainly a good alternative with respect to the literature counterparts.
For the entire collection see [Zbl 1307.62007].

62P30 Applications of statistics in engineering and industry; control charts
62G10 Nonparametric hypothesis testing
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