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随机删失下经验测度的局部收敛及其在密度与风险率估计中的应用AI 解读

In this paper, we study the local deviations of the empirical measure defined by the Kaplan-Meier (1958) estimator for the survival function. The results are applied to derive best rates of convergence for kernel estimators for the density and hazard rate function in the random censorship model.

随机删失下风险率与密度函数的数据自适应核估计札记AI 解读

In a recent paper, Tanner (1983) proves pointwise consistency of a variable bandwidth kernel estimator for the hazard function. In the present note, a simplified proof of uniform consistency of a data-adaptive kernel estimator with certain additional advantages is given.