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A New Kumaraswamy Generalized Family of Distributions with Properties, Applications, and Bivariate Extension

机译:新的Kumaraswamy广泛性的分布系列,具有属性,应用和生物分配

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For bounded unit interval, we propose a new Kumaraswamy generalized (G) family of distributions through a new generator which could be an alternate to the Kumaraswamy-G family proposed earlier by Cordeiro and de Castro in 2011. This new generator can also be used to develop alternate G-classes such as beta-G, McDonald-G, Topp-Leone-G, Marshall-Olkin-G, and Transmuted-G for bounded unit interval. Some mathematical properties of this new family are obtained and maximum likelihood method is used for the estimation of G-family parameters. We investigate the properties of one special model called the new Kumaraswamy-Weibull (NKwW) distribution. Parameters of NKwW model are estimated by using maximum likelihood method, and the performance of these estimators are assessed through simulation study. Two real life data sets are analyzed to illustrate the importance and flexibility of the proposed model. In fact, this model outperforms some generalized Weibull models such as the Kumaraswamy–Weibull, McDonald–Weibull, beta-Weibull, exponentiated-generalized Weibull, gamma-Weibull, odd log-logistic-Weibull, Marshall–Olkin–Weibull, transmuted-Weibull and exponentiated-Weibull distributions when applied to these data sets. The bivariate extension of the family is also proposed, and the estimation of parameters is dealt. The usefulness of the bivariate NKwW model is illustrated empirically by means of a real-life data set.
机译:对于有界单元间隔,我们通过新的发电机提出了一种新的Kumaraswamy广义(G)分布系,这是2011年之前提出的Kumaraswamy-G家族的交替。这个新的发电机也可以用来开发替代G-类,例如Beta-G,McDonald-G,TopP-Leone-G,Marshall-Olkin-G和用于有界单元间隔的传输-G。获得该新系列的一些数学特性,并且最大似然方法用于估计G家族参数。我们调查一个特殊模型的属性,称为新的Kumaraswamy-Weibull(NKWW)分布。通过使用最大似然方法估计NKWW模型的参数,通过仿真研究评估这些估算器的性能。分析了两个真实生活数据集以说明所提出的模型的重要性和灵活性。实际上,这个模型优于一些概述的威布尔模型,如kumaraswamy-weibull,麦克唐纳-Weibull,Beta-Weibull,指数泛化的威布尔,伽玛 - 威布尔,奇数日志逻辑-Wibull,Marshall-Olkin-Weibull,传输 - Weibull并在应用于这些数据集时的exconentiateed-weibull分发。还提出了家庭的双变量扩展,并估计参数。通过现实生活数据集凭经验说明了一致性的NKWW模型的有用性。

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