Package: HistDAWass
Type: Package
Title: Histogram-Valued Data Analysis
Version: 0.1.7
Date: 2017-09-26
Authors@R: c(person("Antonio", "Irpino", role = c("aut", "cre"),
  	     email = "antonio.irpino@unicampania.it"))
Author: Antonio Irpino [aut, cre]
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., 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.
License: GPL (>= 2)
Imports: graphics, class, FactoMineR, ggplot2, grid, histogram,
        grDevices, stats, colorspace, utils
Depends: R(>= 3.1), methods
LazyData: true
Collate: 'All_classes.R' 'Utility.R' 'Fuzzy_cmeans.R' 'H_time_series.R'
        'HistDAWass-package.R' 'Kohonen_maps.R' 'Met_HTS.R'
        'Met_MatH.R' 'Met_distributionH.R' 'principal_components.R'
        'regression.R' 'unsuperv_classification.R'
        'Plotting_with_ggplot.R'
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2017-09-21 15:18:22 UTC; Antonio
Repository: CRAN
Date/Publication: 2017-09-21 20:46:18 UTC
