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A Novel Generalized Family of Distributions for Engineering and Life Sciences Data Applications

机译:工程和生命科学数据应用的新型广义族分布

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In this paper, a new method is proposed to expand the family of lifetime distributions. The suggested method is named as Khalil new generalized family (KNGF) of distributions. A special submodel, termed as Khalil new generalized Pareto (KNGP) distribution, is investigated from the family with one shape and two scale parameters. A number of mathematical properties of the submodel have been derived including moments, moment-generating function, quantile function, entropy measures, order statistics, mean residual life function, and maximum likelihood method for the estimation of parameters. The proposed distribution is very flexible in its nature covering several hazard rate shapes (symmetric and asymmetric). To examine the performance of the maximum likelihood estimates in terms of their bias and mean squared error using simulated samples, a simulation study is carried out. Furthermore, parametric estimation of the model is conferred using the method of maximum likelihood, and the practicality of the proposed family is illustrated with the help of real datasets. Finally, we hope that the new suggested flexible KNGF may produce useful models for fitting monotonic and nonmonotonic data related to survival analysis and reliability analysis.
机译:在本文中,提出了一种新方法来扩大寿命分布的系列。建议的方法被命名为khalil新的广义族(Kngf)的分布。作为Khalil新的广义帕累托(KNGP)分布称为Khalil新的亚模型,由一种形状和两个比例参数研究。已经导出了子模型的许多数学特性,包括矩,矩生成函数,分位数函数,熵测量,顺序统计,平均剩余寿命功能以及用于估计参数的最大似然方法。拟议的分布在其性质上非常灵活,覆盖几种危险率形状(对称和不对称)。在使用模拟样本中检查其偏置和均方误差方面的最大似然估计的性能,进行了模拟研究。此外,使用最大可能性的方法赋予模型的参数估计,并且在实际数据集的帮助下示出了所提出的家庭的实用性。最后,我们希望新的建议的灵活KNGF可以为拟合与生存分析和可靠性分析相关的单调和非单调数据产生有用的模型。

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