robCompositions: Robust Estimation for Compositional Data
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.
| Version: |
2.0.0 |
| Depends: |
R (≥ 2.10), robustbase, ggplot2, data.table, pls |
| Imports: |
e1071, cvTools, rrcov, GGally, MASS, sROC, VIM |
| Suggests: |
knitr |
| Published: |
2016-02-08 |
| Author: |
Matthias Templ, Karel Hron, Peter Filzmoser |
| Maintainer: |
Matthias Templ <templ at tuwien.ac.at> |
| License: |
GPL-2 |
| NeedsCompilation: |
yes |
| Citation: |
robCompositions citation info |
| Materials: |
README NEWS |
| In views: |
OfficialStatistics |
| CRAN checks: |
robCompositions results |
Downloads:
Reverse dependencies: