ddalpha (1.3.4)

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 ). 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.

Maintainer: Oleksii Pokotylo
Author(s): Oleksii Pokotylo [aut, cre], Pavlo Mozharovskyi [aut], Rainer Dyckerhoff [aut], Stanislav Nagy [aut]

License: GPL-2

Uses: class, geometry, MASS, Rcpp, robustbase, sfsmisc
Reverse depends: curveDepth, TukeyRegion
Reverse suggests: recipes

Released over 1 year ago.