ddalpha: Depth-Based Classification and Calculation of Data Depth

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>).

Version: 1.3.15
Depends: R (≥ 2.10), stats, utils, graphics, grDevices, MASS, class, robustbase, sfsmisc, geometry
Imports: Rcpp (≥ 0.11.0)
LinkingTo: BH, Rcpp
Published: 2024-01-12
DOI: 10.32614/CRAN.package.ddalpha
Author: Oleksii Pokotylo [aut, cre], Pavlo Mozharovskyi [aut], Rainer Dyckerhoff [aut], Stanislav Nagy [aut]
Maintainer: Oleksii Pokotylo <alexey.pokotylo at gmail.com>
License: GPL-2
NeedsCompilation: yes
Citation: ddalpha citation info
In views: FunctionalData
CRAN checks: ddalpha results


Reference manual: ddalpha.pdf


Package source: ddalpha_1.3.15.tar.gz
Windows binaries: r-devel: ddalpha_1.3.15.zip, r-release: ddalpha_1.3.15.zip, r-oldrel: ddalpha_1.3.15.zip
macOS binaries: r-release (arm64): ddalpha_1.3.15.tgz, r-oldrel (arm64): ddalpha_1.3.15.tgz, r-release (x86_64): ddalpha_1.3.15.tgz, r-oldrel (x86_64): ddalpha_1.3.15.tgz
Old sources: ddalpha archive

Reverse dependencies:

Reverse depends: curveDepth, TukeyRegion
Reverse imports: Anthropometry, pdSpecEst, RepeatedHighDim
Reverse suggests: butcher, recipes


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