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June, 1993 Renormalizing Upper and Lower Bounds for Integrated Risk in the White Noise Model:
Mark G. Low
Ann. Statist. 21(2): 577-589 (June, 1993). DOI: 10.1214/aos/1176349137

Abstract

Renormalization arguments are used to derive optimal rates of convergence, under integrated squared error loss, for parameter spaces having a certain rectangular structure.

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Mark G. Low. "Renormalizing Upper and Lower Bounds for Integrated Risk in the White Noise Model:." Ann. Statist. 21 (2) 577 - 589, June, 1993. https://doi.org/10.1214/aos/1176349137

Information

Published: June, 1993
First available in Project Euclid: 12 April 2007

zbMATH: 0795.62038
MathSciNet: MR1232505
Digital Object Identifier: 10.1214/aos/1176349137

Subjects:
Primary: 62G07
Secondary: 62C20

Rights: Copyright © 1993 Institute of Mathematical Statistics

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Vol.21 • No. 2 • June, 1993
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