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The Annals of Probability
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A Law of the Logarithm for Kernel Quantile Density Estimators

A law of the logarithm for kernel quantile density estimators
descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 01 Apr 1994Publisher:Institute of Mathematical StatisticsJournal:The Annals of Probability, volume 22 (issn: 0091-1798, Copyright policy )
Authors: Xiang, Xiaojing;

doi: 10.1214/aop/1176988741

A Law of the Logarithm for Kernel Quantile Density Estimators

Abstract

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Keywords

62G30, almost sure uniform convergence, Strong limit theorems, Kaplan-Meier estimator, optimal bandwidths, Quantile density function, kernel quantile density estimator, kernel-type quantile density estimators, strong Gaussian approximation, oscillation modulus, Order statistics; empirical distribution functions, 62G05, 60F15, Nonparametric estimation, random censorship

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Average
Top 10%
Average
Green
hybrid