Evaluation of bootstrap confidence intervals using a new non-normal process capability index

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dc.contributor.authorRao, Gadde Srinivasa
dc.contributor.authorAlbassam, Mohammed
dc.contributor.authorAslam, Muhammad
dc.date.accessioned2020-11-25T07:43:35Z
dc.date.available2020-11-25T07:43:35Z
dc.date.issued2019
dc.descriptionFull text article. Also available at https://doi.org/10.3390/sym11040484en_US
dc.description.abstractThis paper assesses the bootstrap confidence intervals of a newly proposed process capability index (PCI) forWeibull distribution, using the logarithm of the analyzed data. These methods can be applied when the quality of interest has non-symmetrical distribution. Bootstrap confidence intervals, which consist of standard bootstrap (SB), percentile bootstrap (PB), and bias-corrected percentile bootstrap (BCPB) confidence interval are constructed for the proposed method. A Monte Carlo simulation study is used to determine the efficiency of newly proposed index Cpkw over the existing method by addressing the coverage probabilities and average widths. The outcome shows that the BCPB confidence interval is recommended. The methodology of the proposed index has been explained by using the real data of breaking stress of carbon fibers.en_US
dc.identifier.citationRao, G. S., Albassam, M., & Aslam, M. (2019). Evaluation of bootstrap confidence intervals using a new non-normal process capability index. Symmetry, 11(4), 484.en_US
dc.identifier.otherDOI: 10.3390/sym11040484
dc.identifier.urihttp://hdl.handle.net/20.500.12661/2599
dc.language.isoenen_US
dc.publisherMultidisciplinary Digital Publishing Instituteen_US
dc.subjectWeibull distributionen_US
dc.subjectProcess Capability Indexen_US
dc.subjectPCIen_US
dc.subjectPercentile Bootstrapen_US
dc.subjectPBen_US
dc.subjectBootstrap Confidence Intervalsen_US
dc.subjectCoverage probabilitiesen_US
dc.subjectNon-normal process capability indexen_US
dc.subjectBias-Corrected Percentile Bootstrapen_US
dc.subjectBCPBen_US
dc.titleEvaluation of bootstrap confidence intervals using a new non-normal process capability indexen_US
dc.typeArticleen_US
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