Presmoothing in functional linear regression

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2012_statisticasinica_ferraty_presmoothing.pdf (241.51 KB)
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URI: http://hdl.handle.net/10347/18563
ISSN: 1017-0405
E-ISSN: 1996-8507
DOI: 10.5705/ss.2010.085

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2012

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Academia Sinica, Institute of Statistical Science
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In this paper, we consider the functional linear model with scalar response, and explanatory variable valued in a function space. In recent literature, functional principal components analysis (FPCA) has been used to estimate the model parameter. We propose to modify this approach by using presmoothing techniques. For this new estimate, consistency is stated and efficiency by comparison with the standard FPCA estimator is studied. We have also analysed the behaviour of our presmoothed estimator by means of a simulation study and data applications

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Functional linear regression (FLR)| Functional principal components analysis (FPCA)| Nonparametric kernel estimator| Presmoothing

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Ferraty, F., Gonzalez-Manteiga, W., Martinez-Calvo, A., & Vieu, P. (2012). Presmoothing in functional linear regression. Statistica Sinica, 22, 69-94. doi: 10.5705/ss.2010.085

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© 2012 Academia Sinica, Institute of Statistical Science

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Estatística, Análise Matemática e Optimización