|標題:||Accuracy analysis of the percentile method for estimating non normal manufacturing quality|
Pearn, W. L.
Chang, C. S.
Chen, H. C.
Department of Industrial Engineering and Management
|關鍵字:||flexible capability indices;non normal distributions;relative bias;sample percentile estimator;simulation|
|摘要:||Vannman ( 1995) proposed a superstructure C-p(u, v) of capability indices for processes with normal distributions, which include C-p, C-pk, C-pm, and C-pmk as special cases. Pearn and Chen (1997) considered a generalization of C-p(u, v), called C-Np(u, v), to cover processes with non normal distributions. Pearn and Chen ( 1997) also proposed a sample percentile estimator for the generalization C-Np(u , v). In this article, we investigate the performance of the sample percentile estimator. We perform some simulation study, which covers the normal distribution and various non normal distributions including the uniform distribution, chi-square distribution, student's t distributions, F distribution, beta distribution, gamma distribution, Weibull distribution, lognormal distribution, triangular distribution, and Laplace distribution, with selected parameter values. Extensive simulation results, comparisons, and analysis are provided.|
|期刊:||COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION|
|Appears in Collections:||Articles|
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