https://dapr12.r-universe.devRecent package updates in dapr12R-universehttps://github.com/dapr12.pnghttps://dapr12.r-universe.devTue, 06 Oct 2026 12:19:27 GMTdiego.perezruiz@manchester.ac.uk (Diego Andres Perez Ruiz)Exploratory projection pursuit for ordered categorical (ordinal) items. Monotone category scores and a projection direction are estimated jointly by maximizing a weighted characteristic-function discrepancy between the projected joint distribution and the projection implied by item independence with the observed marginal distributions. Fitted category dictionaries and loadings can be frozen and evaluated on held-out data, with a finite-sample-valid held-out permutation test, a refitted permutation test, a variance/shape decomposition of the index and bootstrap stability summaries.https://github.com/r-universe/dapr12/actions/runs/43592710178Tue, 06 Oct 2026 12:19:27 GMTordpp0.1.0successhttps://dapr12.r-universe.devhttps://github.com/dapr12/ordppdiego.perezruiz@manchester.ac.uk (Diego Andrés Pérez Ruiz)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.https://github.com/r-universe/cran/actions/runs/42363434449Thu, 23 Apr 2026 22:05:20 GMTfdclassify0.1.0successhttps://cran.r-universe.devhttps://github.com/cran/fdclassify