Data depth concept offers a variety of powerful and user friendly
tools for robust exploration and inference for multivariate data. The offered
techniques may be successfully used in cases of lack of our knowledge on
parametric models generating data due to their nature. The
package consist of among others implementations of several data depth techniques
involving multivariate quantile-quantile plots, multivariate scatter estimators,
multivariate Wilcoxon tests and robust regressions.
| Version: |
2.1.5 |
| Depends: |
R (≥ 3.0.0), ggplot2, Rcpp (≥ 0.11.2), rrcov, methods, MASS, np |
| Imports: |
lattice, sm, geometry, colorspace, zoo, grDevices |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
mvtnorm, rgl, sn, robustbase, dplyr, RcppArmadillo, xts, covr, testthat, fda, lintr, roxygen2, pkgbuild |
| Published: |
2022-02-03 |
| Author: |
Zygmunt Zawadzki [aut, cre],
Daniel Kosiorowski [aut],
Krzysztof Slomczynski [ctb],
Mateusz Bocian [ctb],
Anna Wegrzynkiewicz [ctb] |
| Maintainer: |
Zygmunt Zawadzki <zygmunt at zstat.pl> |
| BugReports: |
https://github.com/zzawadz/DepthProc/issues |
| License: |
GPL-2 |
| URL: |
https://www.depthproc.zstat.pl/,
https://github.com/zzawadz/DepthProc |
| NeedsCompilation: |
yes |
| SystemRequirements: |
C++11 |
| Citation: |
DepthProc citation info |
| Materials: |
README NEWS ChangeLog |
| CRAN checks: |
DepthProc results |