Lower Bounds for Nonparametric Density Estimation Rates

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Nonparametric
density estimation
mean integrated square error
Cramér-Rao inequality
Physical Sciences and Mathematics

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Abstract

In Wegman's paper [5] on nonparametric density estimation, he states that it would be interesting to show that there is no density estimator which has mean integrated square rate better than O(n-1). The object of this note is to prove such a result, making no arbitrary assumptions about the specific form of the estimator. This proof is given in Section 2. Our method applies to some other measures of error, as we point out in Section 3.

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1978-07-01

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The Annals of Statistics

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At the time of publication, author J. Michael Steele was affiliated with University of British Columbia. Currently, he is a faculty member at the Statistics Department at the University of Pennsylvania.

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