Estimation of the Derivatives of a Function in a Convolution Regression Model with Random Design

Estimation of the Derivatives of a Function in a Convolution Regression Model with Random Design

A convolution regression model with random design is considered. We investigate the estimation of the derivatives of an unknown function, element of the convolution product. We introduce new estimators based on wavelet methods and provide theoretical guarantees on their good performances.

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Veröffentlicht in:Advances in Statistics 2015-03, Vol.2015, p.1-11
Hauptverfasser: Chesneau, Christophe, Kachour, Maher
Format: Artikel
Sprache:eng
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Zusammenfassung:A convolution regression model with random design is considered. We investigate the estimation of the derivatives of an unknown function, element of the convolution product. We introduce new estimators based on wavelet methods and provide theoretical guarantees on their good performances.
ISSN:2356-6892
2314-8314
DOI:10.1155/2015/695904