logitFD: Functional Principal Components Logistic Regression
Functions for fitting a functional principal components logit regression modelin four different situations: ordinary and filtered functional principal componentsof functional predictors, included in the model according to their variabilityexplanation power, and according to their prediction ability by stepwise methods. Theproposed methods were developed in Escabias et al (2004) <doi:10.1080/10485250310001624738> and Escabias et al (2005)<doi:10.1016/j.csda.2005.03.011>.
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