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June, 1992 Renormalization Exponents and Optimal Pointwise Rates of Convergence
David L. Donoho, Mark G. Low
Ann. Statist. 20(2): 944-970 (June, 1992). DOI: 10.1214/aos/1176348665

Abstract

Simple renormalization arguments can often be used to calculate optimal rates of convergence for estimating linear functionals from indirect measurements contaminated with white noise. This allows one to quickly identify optimal rates for certain problems of density estimation, nonparametric regression, signal recovery and tomography. Optimal kernels may also be derived from renormalization; we give examples for deconvolution and tomography.

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David L. Donoho. Mark G. Low. "Renormalization Exponents and Optimal Pointwise Rates of Convergence." Ann. Statist. 20 (2) 944 - 970, June, 1992. https://doi.org/10.1214/aos/1176348665

Information

Published: June, 1992
First available in Project Euclid: 12 April 2007

zbMATH: 0797.62032
MathSciNet: MR1165601
Digital Object Identifier: 10.1214/aos/1176348665

Subjects:
Primary: 62G07
Secondary: 62C20

Rights: Copyright © 1992 Institute of Mathematical Statistics

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Vol.20 • No. 2 • June, 1992
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