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The core pipeline\ncomputes Fraiman-Muniz (FM) functional depth in either its\nTukey or Simplicial variant, derives a signed depth by\ncomparing each curve to a reference median curve via the signed\ndistance integral, and feeds the resulting scalar summary into\nseveral classifiers: the k-Ranked Nearest Neighbour (k-RNN)\nrule, a moving-average smoother, a kernel-density Bayes rule,\nlogistic regression on signed depth and distance to the mode,\nand a generalised additive model (GAM) classifier.\nCross-validation routines for tuning the neighbourhood size k\nand parametric bootstrap confidence intervals are also\nincluded.", "License": "GPL-3", "Encoding": "UTF-8", "Language": "en-GB", "RoxygenNote": "7.3.1", "Config/testthat/edition": "3", "URL": "https://github.com/dapr12/fdclassify", "BugReports": "https://github.com/dapr12/fdclassify/issues", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-08 11:44:59 UTC", "User": "root" }, "Author": "Diego Andrés Pérez Ruiz [aut, cre] 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