The 'HistData' package provides a collection of small data sets
    that are interesting and important in the history of statistics and data
    visualization. The goal of the package is to make these available, both for
    instructional use and for historical research. Some of these present interesting
    challenges for graphics or analysis in R.

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>.

Using the MDL principle, it is possible to estimate
	parameters for a histogram-like model. The package contains
	the implementation of such an estimation method.

Automatic construction of regular and irregular histograms as described in Rozenholc/Mildenberger/Gather (2010).

Provides a number of utility functions useful for
    manipulating large histograms.  This includes methods to trim, subset,
    merge buckets, merge histograms, convert to CDF, and calculate
    information loss due to binning.  It also provides a protocol buffer
    representation of R's native histogram class to allow histograms over
    large data sets to be computed and combined in distributed analytical
    pipelines.  Implements bin-by-bin histogram distance measures
    described in Rubner, Tomasi and Guibas (2000)
    <doi:10.1023/A:1026543900054>, Swain and Ballard (1991)
    <doi:10.1007/BF00130487>, and Puzicha, Hofmann and Buhmann (1997)
    <doi:10.1109/CVPR.1997.609331>, and average shifted histograms as
    in Scott (2015, ISBN:9781118575536).