Package: HistDAWass Type: Package Title: Histogram-Valued Data Analysis Version: 1.0.10 Date: 2026-10-22 Authors@R: c(person(given="Antonio", family= "Irpino", role = c("aut", "cre"), email = "antonio.irpino@unicampania.it", comment = c(ORCID = "0000-0001-9293-7180"))) Maintainer: Antonio Irpino Description: 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) . License: GPL (>= 2) Imports: graphics, class, FactoMineR, ggplot2 (>= 3.4.0), ggridges, grid, histogram, grDevices, stats, utils, Rcpp Suggests: knitr, rmarkdown, testthat (>= 3.0.0) VignetteBuilder: knitr Config/testthat/edition: 3 URL: https://github.com/Airpino/HistDAWass BugReports: https://github.com/Airpino/HistDAWass/issues Depends: R(>= 3.1), methods LazyData: true Collate: 'For_Rccp_int.R' 'All_classes.R' 'RcppExports.R' 'Utility.R' 'Met_HTS.R' 'Met_MatH.R' 'Met_distributionH.R' 'Fuzzy_cmeans.R' 'H_time_series.R' 'HistDAWass-package.R' 'Kohonen_maps.R' 'principal_components.R' 'regression.R' 'unsuperv_classification.R' 'Plotting_with_ggplot.R' Encoding: UTF-8 NeedsCompilation: yes LinkingTo: Rcpp,RcppArmadillo Config/roxygen2/version: 8.1.0 Config/pak/sysreqs: cmake libfreetype6-dev make libicu-dev libpng-dev libuv1-dev zlib1g-dev Repository: https://airpino.r-universe.dev Date/Publication: 2026-10-23 13:54:52 UTC RemoteUrl: https://github.com/airpino/histdawass RemoteRef: HEAD RemoteSha: 65258c765708bae1424fbab87d6b25978c2488bc Packaged: 2026-10-23 15:03:21 UTC; root Author: Antonio Irpino [aut, cre] (ORCID: )