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.
|Author||Antonio Irpino [aut, cre]|
|Date of publication||2017-02-13 11:27:36|
|Maintainer||Antonio Irpino <email@example.com>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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