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Title
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Inference on stress-strength reliability for the generalized exponential distribution based on hybrid censoring scheme
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Type
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Presentation
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Keywords
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Confidence Interval, Generalized Exponential, Distribution Hybrid censoring, scheme Parametric Bootstrap, Stress-Strength Reliability
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Abstract
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Stress-strength reliability is a measure to compare the lifetimes of two systems. One of the most important subjects in the field of life testing is the stress-strength reliability, which always refers to the quantity P(Y < X) in any statistical literature. It resamples a system with random strength (X) that is subjected to a random strength (Y ) such that a system fails in case the stress exceeds the strength. In this study, we consider stress-strength reliability where the strength (X) and stress (Y ) follow generalized exponential distribution. The maximum likelihood estimator of stress-strength reliability and its asymptotic distribution, along with a asymptotic confidence interval and two parametric bootstrap confidence intervals are obtained. A simulation study is performed to compare different estimation procedures and various hybrid censoring schemes. The simulation studies show that asymptotic confidence intervals provide more accurate average lengths of confidence intervals and higher probabilities to contain the true value of the parameter.
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Researchers
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Nooshin Hakamipour (First Researcher)
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