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) and Escabias et al (2005) .


Reference manual

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install.packages("logitFD")

1.0 by Manuel Escabias, 5 years ago


Browse source code at https://github.com/cran/logitFD


Authors: Carmen Lucia Reina <[email protected]> Ana Maria Aguilera <[email protected]> and Manuel Escabias <[email protected]>


Documentation:   PDF Manual  


GPL (>= 2) license


Imports fda, expm, pROC, fda.usc


See at CRAN