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CSDA
2007

Smoothing splines estimators in functional linear regression with errors-in-variables

13 years 11 months ago
Smoothing splines estimators in functional linear regression with errors-in-variables
The Total Least Squares method is generalized in the context of the functional linear model. A smoothing splines estimator of the functional coefficient of the model is first proposed without noise in the covariates and an asymptotic result for this estimator is obtained. Then, this estimator is adapted to the case where the covariates are noisy and an upper bound for the convergence speed is also derived. The estimation procedure is evaluated by means of simulations. Key words Functional Linear Model, Smoothing Splines, Penalization, Errors-in-Variables, Total Least Squares.
Hervé Cardot, Christophe Crambes, Alois Kne
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2007
Where CSDA
Authors Hervé Cardot, Christophe Crambes, Alois Kneip, Pascal Sarda
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