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>.

Version:	1.0
Depends:	R (≥ 3.4.3)
Imports:	fda, expm, pROC, fda.usc
Published:	2022-01-10
DOI:	10.32614/CRAN.package.logitFD
Author:	Carmen Lucia Reina Ana Maria Aguilera and Manuel Escabias
Maintainer:	Manuel Escabias <escabias at ugr.es>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
CRAN checks:	logitFD results

Documentation:

Reference manual:

logitFD.html , logitFD.pdf

Downloads:

Package source:	logitFD_1.0.tar.gz
Windows binaries:	r-devel: logitFD_1.0.zip, r-release: logitFD_1.0.zip, r-oldrel: logitFD_1.0.zip
macOS binaries:	r-release (arm64): logitFD_1.0.tgz, r-oldrel (arm64): logitFD_1.0.tgz, r-release (x86_64): logitFD_1.0.tgz, r-oldrel (x86_64): logitFD_1.0.tgz

Linking:

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