Package: DepthProc
Version: 1.0.7
Date: 2016-02-10
Title: Statistical Depth Functions for Multivariate Analysis
Author: Daniel Kosiorowski, Mateusz Bocian, Anna Wegrzynkiewicz and Zygmunt
Zawadzki from Cracow University of Economics.
Maintainer: Zygmunt Zawadzki <zawadzkizygmunt@gmail.com>
Description: 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 nonparametric 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.
License: GPL-2
Depends: R (>= 3.0.0), ggplot2, Rcpp (>= 0.11.2), rrcov, methods, MASS, np
Imports: lattice, sm, geometry, colorspace,
Suggests: mvtnorm, rgl, sn, robustbase, dplyr, RcppArmadillo
LinkingTo: Rcpp, RcppArmadillo
Repository: CRAN
Repository/R-Forge/Project: depthproc
Repository/R-Forge/Revision: 71
Repository/R-Forge/DateTimeStamp: 2016-02-11 20:18:06
Date/Publication: 2016-02-12 10:59:09
NeedsCompilation: yes
Packaged: 2016-02-11 20:25:29 UTC; rforge
Package: FAiR
Type: Package
Title: Factor Analysis in R
Version: 0.4-15
Date: 2014-02-08
Author: Ben Goodrich
Maintainer: Ben Goodrich <bgokgm@gmail.com>
Description: This package estimates factor analysis models using a
genetic algorithm, which permits a general mechanism for
restricted optimization with arbitrary restrictions that are
chosen at run time with the help of a GUI. Importantly,
inequality restrictions can be imposed on functions of multiple
parameters, which provides a new avenues for testing and
generating theories with factor analysis models. This package
also includes an entirely new estimator of the common factor
analysis model called semi-exploratory factor analysis, which
is a general alternative to exploratory and confirmatory factor
analysis. Finally, this package integrates a lot of other
packages that estimate sample covariance matrices and thus
provides a lot of alternatives to the traditional sample
covariance calculation. Note that you need to have the Gtk run
time library installed on your system to use this package; see
the URL below for detailed installation instructions. Most
users would only need to understand the first twenty-four pages
of the PDF manual.
URL: http://wiki.r-project.org/rwiki/doku.php?id=packages:cran:fair
License: AGPL (>= 3) + file LICENSE
Encoding: UTF-8
Depends: R (>= 2.7.0), methods, rgenoud (>= 5.4-7), gWidgetsRGtk2 (>=
0.0-31), stats4, rrcov, Matrix
Suggests: corpcor, mvnmle, polycor, nFactors, Rgraphviz, mvnormtest, energy, GPArotation, sem, MASS, psych
LazyLoad: yes
Packaged: 2014-02-08 06:13:33 UTC; goodrich
Repository: CRAN
Date/Publication: 2014-02-08 08:06:48
NeedsCompilation: yes
Package: FRB
Type: Package
Title: Fast and Robust Bootstrap
Version: 1.8
Date: 2013-04-15
Author: Ella Roelant, Stefan Van Aelst, Gert Willems
Maintainer: Stefan Van Aelst <Stefan.VanAelst@ugent.be>
Depends: corpcor, rrcov (>= 1.3-01)
Description: This package performs robust inference based on applying
Fast and Robust Bootstrap on robust estimators. Available
methods are multivariate regression, PCA and Hotelling tests.
License: GPL-2
Repository: CRAN
Packaged: 2013-04-16 09:33:54 UTC; svaelst
NeedsCompilation: no
Date/Publication: 2013-04-16 12:42:04
providing 
.