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

Vesa Hasu, Kalle Halmevaara and Heikki Koivo

Journal of Nonparametric Statistics, 2011, vol. 23, issue 2, 399-413

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.

Date: 2011
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DOI: 10.1080/10485252.2010.526210

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