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http://dx.doi.org/10.7465/jkdi.2015.26.6.1353

Robust determination of control parameters in K chart with respect to data structures  

Park, Ingkeun (Department of Applied Statistics, Dankook University)
Lee, Sungim (Department of Applied Statistics, Dankook University)
Publication Information
Journal of the Korean Data and Information Science Society / v.26, no.6, 2015 , pp. 1353-1366 More about this Journal
Abstract
These days Shewhart control chart for evaluating stability of the process is widely used in various field. But it must follow strict assumption of distribution. In real-life problems, this assumption is often violated when many quality characteristics follow non-normal distribution. Moreover, it is more serious in multivariate quality characteristics. To overcome this problem, many researchers have studied the non-parametric control charts. Recently, SVDD (Support Vector Data Description) control chart based on RBF (Radial Basis Function) Kernel, which is called K-chart, determines description of data region on in-control process and is used in various field. But it is important to select kernel parameter or etc. in order to apply the K-chart and they must be predetermined. For this, many researchers use grid search for optimizing parameters. But it has some problems such as selecting search range, calculating cost and time, etc. In this paper, we research the efficiency of selecting parameter regions as data structure vary via simulation study and propose a new method for determining parameters so that it can be easily used and discuss a robust choice of parameters for various data structures. In addition, we apply it on the real example and evaluate its performance.
Keywords
K-chart; kernel parameter; RBF kernel; SVDD control chart;
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Times Cited By KSCI : 3  (Citation Analysis)
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