RT Journal Article
T1 Presmoothing in functional linear regression
A1 Ferraty, Frédéric
A1 González Manteiga, Wenceslao
A1 Martínez Calvo, Adela
A1 Vieu, Philippe
K1 Functional linear regression (FLR)
K1 Functional principal components analysis (FPCA)
K1 Nonparametric kernel estimator
K1 Presmoothing
AB 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
PB Academia Sinica, Institute of Statistical Science
SN 1017-0405
YR 2012
FD 2012
LK http://hdl.handle.net/10347/18563
UL http://hdl.handle.net/10347/18563
LA eng
NO 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
DS Minerva
RD 3 may 2026