A Note on Wavelet Estimation of the Derivatives of a Regression Function in a Random Design Setting

Christophe Chesneau

International Journal of Mathematics and Mathematical Sciences, 2014, vol. 2014, 1-8

Abstract:

We investigate the estimation of the derivatives of a regression function in the nonparametric regression model with random design. New wavelet estimators are developed. Their performances are evaluated via the mean integrated squared error. Fast rates of convergence are obtained for a wide class of unknown functions.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jijmms:195765

DOI: 10.1155/2014/195765

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