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一般随机序约束下生存函数的非参数极大似然估计及其对偶AI 解读

This paper discusses estimation of survival functions under an arbitrary partial stochastic ordering of the underlying populations. This technique is especially useful when data are not easily acquired from one or more of the populations, but data from the other populations are available. Estimation of the ordered survival functions entails use of a Fenchel duality theorem that results in an algorithm to identify and resolve violations of the underlying ordering. The…

一般随机序约束下生存函数的非参数最大似然估计及其对偶AI 解读

This paper discusses estimation of survival functions under an arbitrary partial stochastic ordering of the underlying populations. This technique is especially useful when data are not easily acquired from one or more of the populations, but data from the other populations are available. Estimation of the ordered survival functions entails use of a Fenchel duality theorem that results in an algorithm to identify and resolve violations of the underlying ordering. The…

N 个随机有序变量生存函数的极大似然估计AI 解读

Very often distributions will exist that logically should satisfy linear stochastic ordering requirements. For example, if a mechanical device is improved through N stages, the corresponding survival functions should be linearly stochastically ordered. Nevertheless, estimates may not totally reflect this stochastic ordering because of the inherent variability of the observations. Here we characterize the maximum likelihood estimates of the survival functions subject to…

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