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., a 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.

Version: 0.1.6
Depends: R (≥ 3.1), methods
Imports: graphics, class, FactoMineR, ggplot2, grid, histogram, grDevices, stats, colorspace, utils
Published: 2017-02-13
Author: Antonio Irpino [aut, cre]
Maintainer: Antonio Irpino <antonio.irpino at unina2.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README
CRAN checks: HistDAWass results


Reference manual: HistDAWass.pdf
Package source: HistDAWass_0.1.6.tar.gz
Windows binaries: r-devel: HistDAWass_0.1.6.zip, r-release: HistDAWass_0.1.6.zip, r-oldrel: HistDAWass_0.1.6.zip
OS X El Capitan binaries: r-release: HistDAWass_0.1.6.tgz
OS X Mavericks binaries: r-oldrel: HistDAWass_0.1.6.tgz
Old sources: HistDAWass archive


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