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: 1.0.8
Depends: R (≥ 3.1), methods
Imports: graphics, class, FactoMineR, ggplot2, ggridges, grid, histogram, grDevices, stats, utils, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Published: 2024-01-24
Author: Antonio Irpino ORCID iD [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

Documentation:

Reference manual: HistDAWass.pdf

Downloads:

Package source: HistDAWass_1.0.8.tar.gz
Windows binaries: r-devel: HistDAWass_1.0.8.zip, r-release: HistDAWass_1.0.8.zip, r-oldrel: HistDAWass_1.0.8.zip
macOS binaries: r-release (arm64): HistDAWass_1.0.8.tgz, r-oldrel (arm64): HistDAWass_1.0.8.tgz, r-release (x86_64): HistDAWass_1.0.8.tgz
Old sources: HistDAWass archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=HistDAWass to link to this page.