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An approximation procedure of quantiles using an estimation of kernel method for quality control

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  • Vesa Hasu
  • Kalle Halmevaara
  • Heikki Koivo

Abstract

Testing measurements against quantiles of their distributions is a basic quality control technique. Unfortunately, the methods for the empirical quantile computation require usually ordered observations, which is not feasible for on-line use in large systems. This paper proposes a procedure for approximation of quantiles from a random sample of observations. The procedure is applicable on-line without exhaustive database searches, and it enables also approximation of high quantiles and nonstationary distributions. Our approach is based on using a linear approximation of the kernel smoothed quantile estimation for the cumulative distribution function. We apply the procedure in the quality control of temperature measurement with a tail frequency estimation approach.

Suggested Citation

  • Vesa Hasu & Kalle Halmevaara & Heikki Koivo, 2011. "An approximation procedure of quantiles using an estimation of kernel method for quality control," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(2), pages 399-413.
    • Handle: RePEc:taf:gnstxx:v:23:y:2011:i:2:p:399-413
    DOI: 10.1080/10485252.2010.526210
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    References listed on IDEAS

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    1. Berwin A. TURLACH, "undated". "Bandwidth selection in kernel density estimation: a rewiew," Statistic und Oekonometrie 9307, Humboldt Universitaet Berlin.
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