Revision 608a88e9639a4be776be79af369b32860fc984a7 authored by Matthias Templ on 12 July 2017, 18:31:22 UTC, committed by cran-robot on 12 July 2017, 18:31:22 UTC
1 parent f01abd0
DESCRIPTION
Package: robCompositions
Type: Package
Title: Robust Estimation for Compositional Data
Version: 2.0.5
Date: 2017-06-14
Depends: R (>= 3.0.0), robustbase, ggplot2, data.table, e1071, pls
LinkingTo: Rcpp
Imports: car, rrcov, cluster, cvTools, fpc, GGally, kernlab, MASS,
mclust, Rcpp, sROC, VIM
Suggests: knitr
VignetteBuilder: knitr
Author: Matthias Templ, Karel Hron, Peter Filzmoser
Maintainer: Matthias Templ <matthias.templ@gmail.com>
Description: Methods for analysis of compositional data including robust
methods, imputation, methods to replace rounded zeros, (robust) outlier
detection for compositional data, (robust) principal component analysis for
compositional data, (robust) factor analysis for compositional data, (robust)
discriminant analysis for compositional data (Fisher rule), robust regression
with compositional predictors and (robust) Anderson-Darling normality tests for
compositional data as well as popular log-ratio transformations (addLR, cenLR,
isomLR, and their inverse transformations). In addition, visualisation and
diagnostic tools are implemented as well as high and low-level plot functions
for the ternary diagram.
License: GPL-2
LazyLoad: yes
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-07-12 15:58:20 UTC; teml
Repository: CRAN
Date/Publication: 2017-07-12 19:31:22 UTC
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