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fdclassify  

Supervised Classification for Functional Data via Signed Depth
View on CRAN: Click here


Download and install fdclassify package within the R console
Install from CRAN:
install.packages("fdclassify")

Install from Github:
library("remotes")
install_github("cran/fdclassify")

Install by package version:
library("remotes")
install_version("fdclassify", "0.1.0")



Attach the package and use:
library("fdclassify")
Maintained by
Diego Andrés Pérez Ruiz
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-23
Latest Update: 2026-04-23
Description:
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.
How to cite:
Diego Andrés Pérez Ruiz (2026). fdclassify: Supervised Classification for Functional Data via Signed Depth. R package version 0.1.0, https://cran.r-project.org/web/packages/fdclassify. Accessed 25 Oct. 2026.
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