HistDAWass: Histogram-Valued Data Analysis

In the framework of Symbolic Data Analysis, a relatively new approach to the statistical analysis of multi-valued data, we consider histogram-valued data, i.e., data described by univariate histograms. The methods and the basic statistics for histogram-valued data are mainly based on the L2 Wasserstein metric between distributions, i.e., the Euclidean metric between quantile functions. The package contains unsupervised classification techniques, least square regression and tools for histogram-valued data and for histogram time series. An introducing paper is Irpino A. Verde R. (2015) <doi:10.1007/s11634-014-0176-4>.

Version: 0.1.8
Depends: R (≥ 3.1), methods
Imports: graphics, class, FactoMineR, ggplot2, grid, histogram, grDevices, stats, utils, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Published: 2017-10-06
Author: Antonio Irpino [aut, cre]
Maintainer: Antonio Irpino <antonio.irpino at unicampania.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README
CRAN checks: HistDAWass results

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Reference manual: HistDAWass.pdf
Package source: HistDAWass_0.1.8.tar.gz
Windows binaries: r-devel: HistDAWass_0.1.8.zip, r-release: HistDAWass_0.1.8.zip, r-oldrel: HistDAWass_0.1.8.zip
OS X El Capitan binaries: r-release: HistDAWass_0.1.8.tgz
OS X Mavericks binaries: r-oldrel: HistDAWass_0.1.8.tgz
Old sources: HistDAWass archive

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