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Nearest Neighbor and Kernel Survival Analysis: Nonasymptotic Error Bounds and Strong Consistency Rates. (arXiv:1905.05285v2 [stat.ML] UPDATED)
Sept. 16, 2022, 1:13 a.m. | George H. Chen
stat.ML updates on arXiv.org arxiv.org
We establish the first nonasymptotic error bounds for Kaplan-Meier-based
nearest neighbor and kernel survival probability estimators where feature
vectors reside in metric spaces. Our bounds imply rates of strong consistency
for these nonparametric estimators and, up to a log factor, match an existing
lower bound for conditional CDF estimation. Our proof strategy also yields
nonasymptotic guarantees for nearest neighbor and kernel variants of the
Nelson-Aalen cumulative hazards estimator. We experimentally compare these
methods on four datasets. We find that for …
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