fdclassify
Supervised Classification for Functional Data via Signed Depth
Provides a suite of supervised classifiers for functional data based on the concept of signed depth. The core pipeline computes Fraiman-Muniz (FM) functional depth in either its Tukey or Simplicial variant, derives a signed depth by comparing each curve to a reference median curve via the signed distance integral, and feeds the resulting scalar summary into several classifiers: the k-Ranked Nearest Neighbour (k-RNN) rule, a moving-average smoother, a kernel-density Bayes rule, logistic regression on signed depth and distance to the mode, and a generalised additive model (GAM) classifier. Cross-validation routines for tuning the neighbourhood size k and parametric bootstrap confidence intervals are also included.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | fdclassify_0.1.0.tar.gz |
88.1 KiB |
0.1.0 |
rolling linux/noble R-4.5 | fdclassify_0.1.0.tar.gz |
88.0 KiB |
0.1.0 |
rolling source/ R- | fdclassify_0.1.0.tar.gz |
18.7 KiB |
0.1.0 |
latest linux/jammy R-4.5 | fdclassify_0.1.0.tar.gz |
88.1 KiB |
0.1.0 |
latest linux/noble R-4.5 | fdclassify_0.1.0.tar.gz |
88.0 KiB |
0.1.0 |
latest source/ R- | fdclassify_0.1.0.tar.gz |
18.7 KiB |
0.1.0 |
2026-04-26 source/ R- | fdclassify_0.1.0.tar.gz |
18.7 KiB |
0.1.0 |
2026-04-23 source/ R- | fdclassify_0.1.0.tar.gz |
0 B |