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Bayesian Analysis of Log-Generalized Inverse Weibull Distribution using Ranked set sampling

机译:使用排序集抽样的对数广义逆威布尔分布的贝叶斯分析

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The Weibull distribution is one of the most popular distributions in the lifetime data analyzing because a wide variety of shapes with varying levels of its parameters can be created. During the past decades, extensive work has been done on this distribution in both the frequentist and Bayesian points of view, like, Johnson et al. (1995) and Kundu (2008). Moreover, the Weibull probability density function can be decreasing (or increasing) or unimodal, depending on the shape of distribution parameters. The inverse Weibull distribution (IW) is usually used in reliability and biological studies. The three- parameter generalized inverse Weibull (GIW) distribution, which extends to several distributions, and commonly used in the lifetime-literature, is more flexible than the inverse Weibull distribution. Mudholkar et al. (1994), Jiang et al. (1999) and De Gusmao et al. (2011) introduced and discussed the three-parameter GIW distribution. Helu et al. (2010) discussed Bayes estimation of parameters of weibull distribution using ranked set sampling.
机译:威布尔分布是生命周期数据分析中最受欢迎的分布之一,因为可以创建各种形状的参数,这些形状具有不同的参数水平。在过去的几十年中,从约翰逊等人(Johnson等人)的观点出发,无论是在常人还是在贝叶斯论点上,都已经对该分布进行了大量的工作。 (1995)和昆都(2008)。此外,取决于分布参数的形状,威布尔概率密度函数可以是递减的(或递增的)或单峰的。逆威布尔分布(IW)通常用于可靠性和生物学研究中。三参数广义逆威布尔分布(GIW)扩展到多个分布,并且通常用于终生文学,比逆威布尔分布更灵活。 Mudholkar等。 (1994),Jiang等。 (1999)和De Gusmao等。 (2011年)介绍并讨论了三参数GIW分布。 Helu等。 (2010年)讨论了使用排序集抽样的韦伯分布参数的贝叶斯估计。

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