# Buildsheet autogenerated by ravenadm tool -- Do not edit.

NAMEBASE=		R-ddalpha
VERSION=		1.3.16
KEYWORDS=		cran
VARIANTS=		std
SDESC[std]=		Depth-based classification and calculations
HOMEPAGE=		none
CONTACT=		CRAN_Automaton[cran@ironwolf.systems]

DOWNLOAD_GROUPS=	main
SITES[main]=		CRAN/src/contrib
			https://loki.dragonflybsd.org/cranfiles/
DISTFILE[1]=		ddalpha_1.3.16.tar.gz:main
DIST_SUBDIR=		CRAN
DF_INDEX=		1
SPKGS[std]=		single

OPTIONS_AVAILABLE=	none
OPTIONS_STANDARD=	none

BUILDRUN_DEPENDS=	R-robustbase:single:std
			R-sfsmisc:single:std
			R-geometry:single:std
			R-Rcpp:single:std
			R-BH:single:std

USES=			cran gmake

DISTNAME=		ddalpha

GENERATED=		yes

INSTALL_REQ_TOOLCHAIN=	yes

[FILE:837:descriptions/desc.single]
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 &lt;<a
href="https://doi.org/10.1007%2Fs00362-012-0488-4"
target="_top">doi:10.1007/s00362-012-0488-4</a>&gt;). 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 &lt;<a href="https://doi.org/10.18637%2Fjss.v091.i05"
target="_top">doi:10.18637/jss.v091.i05</a>&gt;).


[FILE:105:distinfo]
3990f8649ffae227233bc0156d43b727486197eeb73a3200019c441a41516984       489959 CRAN/ddalpha_1.3.16.tar.gz