Abstract
The problem of the nonparametric minimax estimation of an infinitely smooth density at a given point, under random censorship, is considered. We establish the exact asymptotics of the local minimax risk and propose the efficient kernel-type estimator based on the well known Kaplan-Meier estimator.
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Belitser, E., Levit, B. Asymptotically Local Minimax Estimation of Infinitely Smooth Density with Censored Data. Annals of the Institute of Statistical Mathematics 53, 289–306 (2001). https://doi.org/10.1023/A:1012418722154
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DOI: https://doi.org/10.1023/A:1012418722154