Modeling environmental data by functional principal component logistic regression

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Prediction in functional linear regression (2006, methodology): “Other recent work on regression for functional data includes that of Ferré and Yao [18], who introduced a functional version of sliced inverse regression; Preda and Saporta [26], who discussed linear regression on clusters of functional data; Escabias, Aguilera and Valderrama [14] and Ratcliffe, He”
Using basis expansions for estimating functional PLS regression Applications with chemometric data (2010, methodology): “Following the ideas introduced in [11] for interpreting the functional logit model in the case of an environmental data application, zones can be found in the functional observation domain in which a constant increase in a functional observation causes a specific change in the response.”
Statistical Computing in Functional Data Analysis: The R Package fda.usc (2012, methodology): “The book by [Ferraty and Vieu (2006)] is another important reference incorporating non-parametric approaches as well as the us of other theoretical tools such as seminorms and small ball probabilities. These authors are part of the French group STAPH maintaining the page http://www.lsp.ups-tlse.fr/s”