Adaptive estimation of an additive regression function from weakly dependent data

Christophe Chesneau, Jalal Fadili and Bertrand Maillot

Journal of Multivariate Analysis, 2015, vol. 133, issue C, 77-94

Abstract: A d-dimensional nonparametric additive regression model with dependent observations is considered. Using the marginal integration technique and wavelets methodology, we develop a new adaptive estimator for a component of the additive regression function. Its asymptotic properties are investigated via the minimax approach under the L2 risk over Besov balls. We prove that it attains a sharp rate of convergence which turns to be the one obtained in the i.i.d. case for the standard univariate regression estimation problem.

Keywords: Additive regression; Dependent data; Adaptivity; Wavelets; Hard thresholding (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (4)

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DOI: 10.1016/j.jmva.2014.09.005

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