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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0 |
rolling linux/jammy R-4.5 | logitFD_1.0.tar.gz |
47.5 KiB |
1.0 |
rolling linux/noble R-4.5 | logitFD_1.0.tar.gz |
47.3 KiB |
1.0 |
rolling source/ R- | logitFD_1.0.tar.gz |
4.8 KiB |
1.0 |
latest linux/jammy R-4.5 | logitFD_1.0.tar.gz |
47.5 KiB |
1.0 |
latest linux/noble R-4.5 | logitFD_1.0.tar.gz |
47.3 KiB |
1.0 |
latest source/ R- | logitFD_1.0.tar.gz |
4.8 KiB |
1.0 |
2026-04-26 source/ R- | logitFD_1.0.tar.gz |
4.8 KiB |
1.0 |
2026-04-23 source/ R- | logitFD_1.0.tar.gz |
4.8 KiB |
1.0 |
2026-04-09 windows/windows R-4.5 | logitFD_1.0.zip |
50.2 KiB |
1.0 |
2025-04-20 source/ R- | logitFD_1.0.tar.gz |
4.8 KiB |