diff options
-rw-r--r-- | math/Makefile | 1 | ||||
-rw-r--r-- | math/R-cran-ddalpha/Makefile | 22 | ||||
-rw-r--r-- | math/R-cran-ddalpha/distinfo | 3 | ||||
-rw-r--r-- | math/R-cran-ddalpha/pkg-descr | 10 |
4 files changed, 36 insertions, 0 deletions
diff --git a/math/Makefile b/math/Makefile index a18ecdf7e881..a3e9130d5318 100644 --- a/math/Makefile +++ b/math/Makefile @@ -36,6 +36,7 @@ SUBDIR += R-cran-car SUBDIR += R-cran-coda SUBDIR += R-cran-combinat + SUBDIR += R-cran-ddalpha SUBDIR += R-cran-deldir SUBDIR += R-cran-dimRed SUBDIR += R-cran-dlmodeler diff --git a/math/R-cran-ddalpha/Makefile b/math/R-cran-ddalpha/Makefile new file mode 100644 index 000000000000..44907501a889 --- /dev/null +++ b/math/R-cran-ddalpha/Makefile @@ -0,0 +1,22 @@ +# Created by: TAKATSU Tomonari <tota@FreeBSD.org> +# $FreeBSD$ + +PORTNAME= ddalpha +PORTVERSION= 1.2.1 +CATEGORIES= math +DISTNAME= ${PORTNAME}_${PORTVERSION} + +MAINTAINER= tota@FreeBSD.org +COMMENT= Depth-Based Classification and Calculation of Data Depth + +LICENSE= GPLv2 + +CRAN_DEPENDS= R-cran-robustbase>0:math/R-cran-robustbase \ + R-cran-Rcpp>=0.11.0:devel/R-cran-Rcpp \ + R-cran-BH>0:devel/R-cran-BH +BUILD_DEPENDS= ${CRAN_DEPENDS} +RUN_DEPENDS= ${CRAN_DEPENDS} + +USES= cran:auto-plist,compiles + +.include <bsd.port.mk> diff --git a/math/R-cran-ddalpha/distinfo b/math/R-cran-ddalpha/distinfo new file mode 100644 index 000000000000..8abd3ed45c0d --- /dev/null +++ b/math/R-cran-ddalpha/distinfo @@ -0,0 +1,3 @@ +TIMESTAMP = 1505038914 +SHA256 (ddalpha_1.2.1.tar.gz) = c4a9842e9dec1bd992460e6c68b5f2f5d6463d0c2474ef2e0e572dd34b284d5b +SIZE (ddalpha_1.2.1.tar.gz) = 417557 diff --git a/math/R-cran-ddalpha/pkg-descr b/math/R-cran-ddalpha/pkg-descr new file mode 100644 index 000000000000..a17a6f3fcc1c --- /dev/null +++ b/math/R-cran-ddalpha/pkg-descr @@ -0,0 +1,10 @@ +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. + +WWW: https://cran.r-project.org/web/packages/ddalpha/ |