Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/22947
Authors: 
Kneip, Alois
Crambes, Christophe
Cardot, Herve
Sarda, Pascal
Year of Publication: 
2006
Series/Report no.: 
Bonn econ discussion papers 2006,2
Abstract: 
This work deals with a generalization of the Total Least Squares method in the context of the functional linear model. We first propose a smoothing splines estimator of the functional coefficient of the model without noise in the covariates and we obtain an asymptotic result for this estimator. Then, we adapt this estimator to the case where the covariates are noisy and we also derive an upper bound for the convergence speed. Our estimation procedure is evaluated by means of simulations.
Subjects: 
Functional Linear Model
Smoothing Splines
Penalization
Errors-in-Variables
Total Least Squares
Document Type: 
Working Paper

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