logitFD: Functional Principal Components Logistic Regression

Functions for fitting a functional principal components logit regression model in four different situations: ordinary and filtered functional principal components of functional predictors, included in the model according to their variability explanation power, and according to their prediction ability by stepwise methods. The proposed 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>.

Getting started

Package details

AuthorCarmen Lucia Reina <carmenlureina@gmail.com> Ana Maria Aguilera <aaguiler@ugr.es> and Manuel Escabias <escabias@ugr.es>
MaintainerManuel Escabias <escabias@ugr.es>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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logitFD documentation built on Jan. 10, 2022, 9:06 a.m.