NDLI: Bootstrap Confidence Intervals of the Modified Process Capability Index for Weibull distribution

Content Provider	Springer Nature Link
Author	Kashif, Muhammad Aslam, Muhammad Rao, G. Srinivasa AL Marshadi, Ali Hussein Jun, Chi Hyuck
Copyright Year	2017
Abstract	The objective of the paper is to modify the existing process capability index (PCI) for a Weibull distribution and to construct bootstrap confidence intervals (BCIs) for the newly proposed index. Three BCIs that consist of standard, percentile and bias-corrected percentile bootstrap (BCPB) confidence intervals are constructed for the newly proposed index and the existing Pearn and Chen index. The efficiency of the newly proposed index $$C_{\mathrm{GPK}} $$ is compared with Pearn and Chen index using their coverage probabilities and average widths. The coverage probabilities and average width of three BCIs were calculated using Monte Carlo simulation studies. The newly proposed index shows better performance than Pearn and Chen index. The results indicate that BCPB confidence interval was more efficient in both cases and outperform other two confidence intervals in all situations. The comparison of average width of BCPB apparently shows that the proposed index performed better in all cases. A real-life example is also provided for a practical application.
Starting Page	4565
Ending Page	4573
Page Count	9
File Format	PDF
ISSN	2193567X
Journal	Arabian Journal for Science and Engineering
Volume Number	42
Issue Number	11
e-ISSN	21914281
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2017-05-03
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bootstrap Process capability index Confidence intervals Weibull distribution Engineering Science, Humanities and Social Sciences, multidisciplinary
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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