A. Kohansal, Carlos J. Pérez-González, Arturo J. Fernández
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引用次数: 0
Abstract
This paper studies the statistical estimation of the stress-strength reliability of multi-component systems under the progressive first failure censoring samples, where the lifetime distribution of each component follows the modified Kumaraswamy distribution. Both the point and interval estimations of the parameters in the reliability function are considered. To this aim, some estimations such as maximum likelihood estimation (MLE), asymptotic confidence intervals, uniformly minimum variance unbiased estimation (UMVUE), approximate Bayes estimation, and highest posterior density (HPD) intervals are obtained. By employing the Monte Carlo simulation, comparison of the performance between different estimates is provided. The paper then analyzes a case study for illustration of the proposed method.
期刊介绍:
The Journal of Risk and Reliability is for researchers and practitioners who are involved in the field of risk analysis and reliability engineering. The remit of the Journal covers concepts, theories, principles, approaches, methods and models for the proper understanding, assessment, characterisation and management of the risk and reliability of engineering systems. The journal welcomes papers which are based on mathematical and probabilistic analysis, simulation and/or optimisation, as well as works highlighting conceptual and managerial issues. Papers that provide perspectives on current practices and methods, and how to improve these, are also welcome