Local linear regression for functional predictor and scalar response

Amparo Baíllo

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

Abstract: The aim of this work is to introduce a new nonparametric regression technique in the context of functional covariate and scalar response. We propose a local linear regression estimator and study its asymptotic behaviour. Its finite-sample performance is compared with a Nadayara-Watson type kernel regression estimator via a Monte Carlo study and the analysis of two real data sets. In all the scenarios considered, the local linear regression estimator performs better than the kernel one, in the sense that the mean squared prediction error and its standard deviation are lower.

Keywords: Functional; data; Nonparametric; smoothing; Local; linear; regression; Kernel; regression; Fourier; expansion; Cross-validation (search for similar items in EconPapers)
Date: 2007-08
New Economics Papers: this item is included in nep-ecm
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Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:ws076115

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