Depth-Based Classification and Calculation of Data Depth R package ddalpha version 1.3.16 CRAN Task View: AnomalyDetection (https://CRAN.R-project.org/view=AnomalyDetection) CRAN Task View: FunctionalData (https://CRAN.R-project.org/view=FunctionalData) Contains procedures for depth-based supervised learning, which are entirely non-parametric, in particular the DDalpha-procedure (Lange, Mosler and Mozharovskyi, 2014 <doi:10.1007/s00362-012-0488-4>). The training data sample is transformed by a statistical depth function to a compact low-dimensional space, where the final classification is done. It also offers an extension to functional data and routines for calculating certain notions of statistical depth functions. 50 multivariate and 5 functional classification problems are included. (Pokotylo, Mozharovskyi and Dyckerhoff, 2019 <doi:10.18637/jss.v091.i05>). Software Depends: R (>= 2.10), stats, utils, graphics, grDevices, MASS, class, robustbase, sfsmisc, geometry Imports: Rcpp (>= 0.11.0) LinkingTo: BH, Rcpp Oleksii Pokotylo <alexey.pokotylo@gmail.com> Comprehensive R Archive Network (CRAN) Oleksii Pokotylo [aut, cre], Pavlo Mozharovskyi [aut], Rainer Dyckerhoff [aut], Stanislav Nagy [aut] GPL-2 2024-09-30 application/tgz https://CRAN.R-project.org/package=ddalpha doi:10.32614/CRAN.package.ddalpha