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Phone: (843) 766-6635
Folly Beach Library
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Edgar Allan Poe/Sullivan's Island Library
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Wando Mount Pleasant Library
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Village Library
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St. Paul's/Hollywood Library
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McClellanville Library
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Hurd/St. Andrews Library
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Classical and Bayesian Inference of a Progressive-Stress Model for the Nadarajah–Haghighi Distribution with Type II Progressive Censoring and Different Loss Functions.
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- Author(s): Alotaibi, Refah; Alamri, Faten S.; Almetwally, Ehab M.; Wang, Min; Rezk, Hoda
- Source:
Mathematics (2227-7390); May2022, Vol. 10 Issue 9, p1602-1602, 19p- Subject Terms:
- Source:
- Additional Information
- Abstract: Accelerated life testing (ALT) is a time-saving technology used in a variety of fields to obtain failure time data for test units in a fraction of the time required to test them under normal operating conditions. This study investigated progressive-stress ALT with progressive type II filtering with the lifetime of test units following a Nadarajah–Haghighi (NH) distribution. It is assumed that the scale parameter of the distribution obeys the inverse power law. The maximum likelihood estimates and estimated confidence intervals for the model parameters were obtained first. The Metropolis–Hastings (MH) algorithm was then used to build Bayes estimators for various squared error loss functions. We also computed the highest posterior density (HPD) credible ranges for the model parameters. Monte Carlo simulations were used to compare the outcomes of the various estimation methods proposed. Finally, one data set was analyzed for validation purposes. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Mathematics (2227-7390) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Abstract:
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