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

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dc.creator Rao, Gadde Srinivasa
dc.creator Albassam, Mohammed
dc.creator Aslam, Muhammad
dc.date 2020-11-25T07:43:35Z
dc.date 2020-11-25T07:43:35Z
dc.date 2019
dc.date.accessioned 2022-10-20T13:25:32Z
dc.date.available 2022-10-20T13:25:32Z
dc.identifier Rao, G. S., Albassam, M., & Aslam, M. (2019). Evaluation of bootstrap confidence intervals using a new non-normal process capability index. Symmetry, 11(4), 484.
dc.identifier DOI: 10.3390/sym11040484
dc.identifier http://hdl.handle.net/20.500.12661/2599
dc.identifier.uri http://hdl.handle.net/20.500.12661/2599
dc.description Full text article. Also available at https://doi.org/10.3390/sym11040484
dc.description This 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.
dc.language en
dc.publisher Multidisciplinary Digital Publishing Institute
dc.subject Weibull distribution
dc.subject Process Capability Index
dc.subject PCI
dc.subject Percentile Bootstrap
dc.subject PB
dc.subject Bootstrap Confidence Intervals
dc.subject Coverage probabilities
dc.subject Non-normal process capability index
dc.subject Bias-Corrected Percentile Bootstrap
dc.subject BCPB
dc.title Evaluation of bootstrap confidence intervals using a new non-normal process capability index
dc.type Article


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