Package: HistDAWass
Type: Package
Title: Histogram-Valued Data Analysis
Version: 1.0.7
Date: 2022-09-26
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 <antonio.irpino@unicampania.it>
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) <doi: 10.1007/s11634-014-0176-4>.
License: GPL (>= 2)
Imports: graphics, class, FactoMineR, ggplot2, ggridges, grid,
        histogram, grDevices, stats, utils, Rcpp, plyr
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
RoxygenNote: 7.2.1
NeedsCompilation: yes
LinkingTo: Rcpp,RcppArmadillo
Packaged: 2022-09-26 08:34:17 UTC; AntonioYOGA
Author: Antonio Irpino [aut, cre] (<https://orcid.org/0000-0001-9293-7180>)
Repository: CRAN
Date/Publication: 2022-09-26 09:40:02 UTC
Built: R 4.2.0; aarch64-apple-darwin20; 2022-09-26 10:15:48 UTC; unix
Archs: HistDAWass.so.dSYM
