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Admissible mixing distributions for a general class of mixture survival models with known asymptotics

机译:具有已知渐近线的一般类别的混合物存活模型的容许混合分布

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Statistical analysis of data on the longest living humans leaves room for speculation whether the human force of mortality is actually leveling off. Based on this uncertainty, we study a mixture failure model, introduced by Finkelstein and Esaulova (2006) that generalizes, among others, the proportional hazards and accelerated failure time models. In this paper we first, extend the Abelian theorem of these authors to mixing distributions, whose densities are functions of regular variation. In addition, taking into account the asymptotic behavior of the mixture hazard rate prescribed by this Abelian theorem, we prove three Tauberian-type theorems that describe the class of admissible mixing distributions. We illustrate our findings with examples of popular mixing distributions that are used to model unobserved heterogeneity
机译:对寿命最长的人类的数据进行统计分析,使人们有可能推测人类的死亡率是否实际上已经趋于稳定。基于这种不确定性,我们研究了Finkelstein和Esaulova(2006)引入的混合失效模型,该模型概括了比例风险和加速失效时间模型。在本文中,我们首先将这些作者的阿贝尔定理扩展到混合分布,其密度是规则变化的函数。此外,考虑到该阿贝尔定理所规定的混合危险率的渐近行为,我们证明了描述陶氏混合分布类别的三个陶伯定理。我们用一些流行的混合分布示例来说明我们的发现,这些分布用于建模未观察到的异质性

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