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 |
| 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:
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