新型瑞利柔性威布尔扩展(RFWE)分布及其在真实和模拟数据中的应用

IF 0.8 Q3 ENGINEERING, MULTIDISCIPLINARY Modelling and Simulation in Engineering Pub Date : 2022-10-22 DOI:10.1155/2022/7718284
Muneeb Javed, S. M. Asim, A. Khalil, Said Farooq Shah, Z. Almaspoor
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引用次数: 0

摘要

Rayleigh柔性威布尔扩展(RFWE)分布是对柔性威布尔扩展的推广,是一种新的三参数模型。该模型对电子设备故障时间的拟合效果最好,该时间是由电子风暴期间电力联动电压峰值得到的。我们推导了RFWE分布的统计性质。用极大似然法估计了新分布的参数,得到了渐近置信限。用真实数据和模拟数据对该模型进行了检验。在各种先验条件下,还进行了额外的贝叶斯估计。通过模拟计算贝叶斯估计和其他后验结果。
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New Rayleigh Flexible Weibull Extension (RFWE) Distribution with Applications to Real and Simulated Data
The Rayleigh flexible Weibull extension (RFWE) distribution, a new three-parameter model introduced in this paper, is a generalization of the flexible Weibull extension. This model produces best fit for failure time of electronic device obtained from power-linkage voltage spikes during electronic storms. We derive the statistical properties of the RFWE distribution. The parameters of this new distribution are estimated using the maximum likelihood method, which also yielded asymptotic confidence bounds. This model is examined using both real and simulated data. Under various priors, an additional Bayesian estimate is also carried out. The Bayes estimates and other posterior results are calculated using simulations.
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来源期刊
Modelling and Simulation in Engineering
Modelling and Simulation in Engineering ENGINEERING, MULTIDISCIPLINARY-
CiteScore
2.70
自引率
3.10%
发文量
42
审稿时长
18 weeks
期刊介绍: Modelling and Simulation in Engineering aims at providing a forum for the discussion of formalisms, methodologies and simulation tools that are intended to support the new, broader interpretation of Engineering. Competitive pressures of Global Economy have had a profound effect on the manufacturing in Europe, Japan and the USA with much of the production being outsourced. In this context the traditional interpretation of engineering profession linked to the actual manufacturing needs to be broadened to include the integration of outsourced components and the consideration of logistic, economical and human factors in the design of engineering products and services.
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