Parametric Lower Confidence Limits of Quantile-Based Process Capability Indices

被引:24
|
作者
Peng, Cheng [1 ]
机构
[1] Univ So Maine, Dept Math & Stat, Portland, ME 04103 USA
来源
关键词
Asymptotic and bootstrap confidence intervals; Kolmogorov-Smirnov goodness-of-fit test; maximum likelihood estimation; process capability index; quantile;
D O I
10.1080/16843703.2010.11673228
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
We consider a construction the parametric asymptotic and bootstrap lower confidence limits for the basic quantile-based process capability indices (PCIs) based on the unified superstructure C(Np) (u, v). The process quantiles are estimated using maximum likelihood estimation and the maximum likelihood estimator of C(Np) (u, v) is proposed. We also proved that the MLE of C(Np) (u, v) is asymptotically normally distributed. A general guideline of selecting the appropriate type of confidence limits is provided. Numerical examples based on real-life data are presented to illustrate the steps of implementing the proposed procedures.
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页码:199 / 214
页数:16
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