Many papers deal with structural testing procedures in multivariate regression. More recently, various estimators have been proposed for regression models involving functional explanatory variables. Thanks to these new estimators, we propose a theoretical framework for structural testing...

Additive model and estimates for regression problems involving functional data are proposed. The impact of the additive methodology for analyzing datasets involving various functional covariates is underlined by comparing its predictive power with those of standard (i.e. non additive)...

This paper focuses on combining association measures using corresponding receiver operating characteristic curves. The approach is motivated by a problem of automatic bigram collocation extraction from the field of computational linguistics. It is based on supervised machine learning techniques...

Additive principal components(APCs) generalize classicalprincipal component analysisto additive nonlinear transformations.Smallest APCsare additive functions of the vectorX=(X1, ..., Xp) minimizing the variance under orthogonality constraints and are characterized as eigenfunctions of an...