Imports: graphics, FactoMineR, class, ggplot2, grid, histogram

Imports: graphics, class, FactoMineR, ggplot2, grid, histogram,

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
between quantile functions. The package contains unsupervised classification
techniques, least square regression and tools for histogram-valued data and for

Collate: 'All_classes.R' 'Utility.R' 'Fuzzy_cmeans.R' 'H_time_series.R'

on the L2 Wasserstein metric between distributions, i.e., the Euclidean metric
histogram time series. An introducing paper is Irpino A. Verde R. (2015) <doi:10.1007/s11634-014-0176-4>.
Collate: 'For_Rccp_int.R' 'All_classes.R' 'RcppExports.R' 'Utility.R'

Imports: graphics, class, FactoMineR, ggplot2, ggridges, grid,
histogram, grDevices, stats, utils, Rcpp

Packaged: 2019-06-04 10:16:08 UTC; AntonioYOGA

Packaged: 2020-02-17 17:59:05 UTC; AntonioYOGA
Author: Antonio Irpino [aut, cre] (<https://orcid.org/0000-0001-9293-7180>)

histogram time series. An introducing paper is Irpino A. Verde R. (2015) \doi{10.1007/s11634-014-0176-4}.
Packaged: 2021-05-24 15:53:51 UTC; AntonioYOGA

histogram time series. An introducing paper is Irpino A. Verde R. (2015) <doi: 10.1007/s11634-014-0176-4>.
Packaged: 2021-06-22 16:42:33 UTC; AntonioYOGA

histogram, grDevices, stats, utils, Rcpp, plyr
Packaged: 2022-09-26 08:34:17 UTC; AntonioYOGA

Title: Summary Statistics for Histogram/Count Data
Description: In some cases you will have data in a histogram format, where
you have a vector of all possible observations, and a vector of how many
times each observation appeared. You could expand this into a single 1D
vector, but this may not be advisable if the counts are extremely large.
'HistDat' allows for the calculation of summary statistics without the need

Suggests: knitr, rmarkdown, testthat (>= 3.0.0),