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On the Flexibility of a Transmuted Type I Generalized Half Logistic Distribution with Application

机译:关于传输类型I的灵活性,我用应用程序的全面半逻辑分布

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In this article we transmute the type I half logistic distribution using quadratic rank transmutation map to develop a transmuted type I half logistic distribution. The quadratic rank transmutation map enables the introduction of extra parameter into its baseline distribution to enhance more flexibility in the analysis of data in various disciplines such as reliability analysis in engineering, survival analysis, medicine, biological sciences, actuarial science, finance and insurance. The mathematical properties such as moments, quantile, mean, median, variance, skewness and kurtosis of this distribution are discussed. The reliability and hazard functions of the transmuted type I half logistic distribution are obtained. The probability density functions of the minimum and maximum order statistics of the transmuted type I half logistic distribution are established and the relationships between the probability density functions of the minimum and maximum order statistics of the parent model and the probability density function of the transmuted type I half logistic distribution are considered. The parameter estimation is done by the method of maximum likelihood estimation. The flexibility of the model in statistical data analysis and its applicability is demonstrated by using it to fit relevant data. The study is concluded by demonstrating that the transmuted type I half logistic distribution has a better goodness of fit than its parent model. We hope this model will serve as an alternative to the existing ones in the literature in fitting positive real data.
机译:在本文中,我们使用二次等级嬗变图传输I型半逻辑分布,以开发传输类型的I.半逻辑分布。二次等级嬗变映射使得能够将额外参数引入其基线分布,以提高各种学科的数据分析中的更多灵活性,例如在工程,生存分析,医学,生物科学,精算科学,金融和保险中的可靠性分析中的可靠性分析。讨论了这种分布的矩,分量,平均值,中值,方差,偏差,偏差和峰值的数学属性。获得了透射型I半逻辑分布的可靠性和危害功能。建立了透射型I半逻辑分布的最小和最大顺序统计的概率密度函数,并且父模型的最小和最大阶统计的概率密度函数与传输类型的概率密度函数之间的关系考虑半逻辑分布。参数估计由最大似然估计的方法完成。通过使用它来符合相关数据,证明了模型在统计数据分析中的灵活性及其适用性。通过证明透明类型的一半逻辑分布具有比其父模型更好的合适的良好优异的研究。我们希望这种模式将作为拟合实际数据的文献中的现有人的替代品。

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