Pascal Sarda

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  • Herv, Cardot Fr, Ed Eric Ferraty, Andr E Mas, Pascal Sarda
  • 2003
The functional linear model with scalar response is a regression model where the predictor is a random function deened on some compact set of R and the response a scalar. The response is modelled as Y = (X) + ", where is some linear continuous operator deened on the space of square integrable functions and valued in R. The random input X is independent from(More)
This paper deals with a linear model of regression on quantiles when the explanatory variable takes values in some functional space and the response is scalar. We propose a spline estimator of the functional coefficient that minimizes a penalized L 1 type criterion. Then, we study the asymptotic behavior of this estimator. The penalization is of primary(More)
The article is devoted to a regression setting where both, the response and the predictor, are random functions defined on some compact sets of R. We consider functional linear (auto)regression and we face the estimation of a bivariate functional parameter. Conditions for existence and uniqueness of the parameter are given and an estimator based on a(More)
Using former maps, geographers intend to study the evolution of the land cover in order to have a prospective approach on the future landscape; predictions of the future land cover, by the use of older maps and environmental variables, are usually done through the GIS (Geographic Information System). We propose here to confront this classical geographical(More)
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