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Analyzing survival data with highly negatively skewed distribution: The Gompertz-sinh family

机译:使用高度负偏斜分布分析生存数据:Gompertz-sinh系列

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In this article, we explore a new two-parameter family of distribution, which is derived by suitably replacing the exponential term in the Gompertz distribution with a hyperbolic sine term. The resulting new family of distribution is referred to as the Gompertz-sinh distribution, and it possesses a thicker and longer lower tail than the Gompertz family, which is often used to model highly negatively skewed data. Moreover, we introduce a useful generalization of this model by adding a second shape parameter to accommodate a variety of density shapes as well as nondecreasing hazard shapes. The flexibility and better fitness of the new family, as well as its generalization, is demonstrated by providing well-known examples that involve complete, group, and censored data.
机译:在本文中,我们探索了一个新的两参数分布族,该族是通过用双曲正弦项适当替换Gompertz分布中的指数项而得出的。由此产生的新的分布族称为Gompertz-sinh分布,它比Gompertz系列具有更粗,更长的尾巴,后者通常用于建模高度负偏斜的数据。此外,我们通过添加第二个形状参数以适应各种密度形状以及不减小的危险形状,对该模型进行了有益的概括。通过提供涉及完整,分组和审查数据的众所周知的示例,可以证明新家族的灵活性和更好的适用性,以及它的概括性。

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