Moments, errors, asymptotic normality and large deviation principle in nonparametric functional regression

Gery Geenens

Statistics & Probability Letters, 2015, vol. 107, issue C, 369-377

Abstract: Recently, some nonparametric regression ideas have been extended to the functional context, allowing infinite-dimensional regressors. This paper gives a deep asymptotic study of the functional Nadaraya–Watson estimator, including moments of all orders, errors, asymptotic distribution and large deviation rate.

Keywords: Nonparametric regression; Functional regression; Scalar-on-function regression; Nadaraya–Watson estimator; Semi-metric (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.spl.2015.09.015

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