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Classical and Bayes estimation of reliability characteristics of the Kumaraswamy-Inverse Exponential distribution

机译:Kumaraswamy-逆指数分布的可靠性特征的经典和贝叶斯估计

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In this research, the Bayesian estimators of both the unknown model parameters, survivor (or reliability) function and failure rate of the three-parameter Kumaraswamy-Inverse Exponential distribution were obtained. The symmetric and asymmetric loss functions were used for the Bayesian estimations. Though, the Bayes estimators could not be obtained in explicit forms. Random samples were generated from the posterior distributions using the Metropolis Hastings algorithm procedure and the Bayes estimators were obtained. Comparison was made between the Bayes estimators and the maximum likelihood estimators using Monte Carlo simulations. In addition, the Bayes estimators of the reliability characteristics were all obtained whilst making use of both the symmetric and asymmetric loss functions. However, their performance was compared through their simulated risks. Furthermore, a numerical study was conducted in order to compare the proposed estimates using simulations while illustrative examples were also presented. Two real life data sets were analyzed for the case when all the three parameters are unknown.
机译:在这项研究中,获得了三参数Kumaraswamy-逆指数分布的未知模型参数,幸存者(或可靠性)函数和失效率的贝叶斯估计。对称损失函数和非对称损失函数用于贝叶斯估计。但是,无法以显式形式获得贝叶斯估计量。使用Metropolis Hastings算法程序从后验分布中生成随机样本,并获得贝叶斯估计量。使用蒙特卡洛模拟对贝叶斯估计量和最大似然估计量进行了比较。此外,在使用对称和非对称损失函数的同时,均获得了可靠性特征的贝叶斯估计量。但是,通过模拟风险比较了它们的性能。此外,进行了数值研究,以便使用模拟比较建议的估算值,同时还提供了说明性示例。当三个参数都未知时,分析了两个实际数据集。

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