Likelihood and Bayesian Inference of the Stress-Strength Reliability Based on Record Values from Proportional and Proportional Reversed Hazard Rate Models
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Nahid Sanjari Farsipour *, Hajar Riyahi |
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Abstract: (18618 Views) |
In this paper the likelihood and Bayesian inference of the stress-strength reliability are considered based on record values from proportional and proportional reversed hazard rate models. Then inference of the stress-strength reliability based on lower record values from some generalized distributions are also considered. Next the likelihood and Bayesian inference of the stress-strength model based on upper record values from Gompertz, Burr type XII, Lomax and Weibull distributions are considered. The ML estimators and their properties are studied. Likelihood-based confidence intervals, exact, as well as the Bayesian credible sets and bootstrap interval for the stress-strength reliability in all distributions are obtained. Simulation studies are conducted to investigate and compare the performance of the intervals. |
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Keywords: Proportional Hazard Rate Model, Proportional Reversed Hazard Rate Model, Record Values, Stress-Strength Model, Bootstrap Interval |
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Full-Text [PDF 509 kb]
(3045 Downloads)
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Type of Study: Research |
Subject:
Statistical Inference Received: 2013/08/28 | Accepted: 2014/04/3 | Published: 2014/04/3
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