Asymptotically local minimax estimation of infinitely smooth density with censored data

E. Belitser, B.Y. Levit

    Research output: Contribution to journalArticleAcademicpeer-review

    8 Citations (Scopus)

    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. Key words and phrases: Efficient estimator, local minimax risk, Kaplan-Meier estimator, kernel, random censorship.
    Original languageEnglish
    Pages (from-to)289-306
    Number of pages18
    JournalAnnals of the Institute of Statistical Mathematics
    Volume53
    Issue number2
    DOIs
    Publication statusPublished - 2001

    Fingerprint

    Dive into the research topics of 'Asymptotically local minimax estimation of infinitely smooth density with censored data'. Together they form a unique fingerprint.

    Cite this