Regression with random design: A minimax study

The problem of estimating a regression function based on a regression model with (known) random design is considered. By adopting the framework of wavelet analysis, we establish the asymptotic minimax rate of convergence under the risk over Besov balls. A part of this paper is devoted to the case where the design density is vanishing.

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Year of publication:	2007
Authors:	Chesneau, Christophe
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 77.2007, 1, p. 40-53
Publisher:	Elsevier
Keywords:	Regression with random design Minimax rate of convergence Besov spaces

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005319446