% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{french_agriculture.hist}
\alias{french_agriculture.hist}
\title{French Agriculture Histogram-Valued Dataset}
\format{
A data frame with 22 observations (French regions) and 4
histogram-valued variables:
\itemize{
    \item \code{Y_TSC}: Histogram of total standard coefficient.
    \item \code{X_Wheat}: Histogram of wheat production.
    \item \code{X_Pig}: Histogram of pig production.
    \item \code{X_Cmilk}: Histogram of cow milk production.
}
Row names are French region names (e.g., Ile-de-France, Picardie).
}
\source{
HistDAWass R package (\code{Agronomique} dataset).
}
\usage{
data(french_agriculture.hist)
}
\description{
Histogram-valued dataset of 22 French regions with 4 economic
histogram variables related to agricultural production. Each histogram
describes the distribution of farm-level values within a region.
}
\section{Metadata}{

\tabular{ll}{
  \strong{Sample size (n)} \tab 22 \cr
  \strong{Variables (p)} \tab 4 \cr
  \strong{Subject area} \tab Agriculture \cr
  \strong{Symbolic format} \tab Histogram \cr
  \strong{Analytical tasks} \tab Regression, Clustering
}
}

\examples{
data(french_agriculture.hist)
}
\references{
Irpino, A. and Verde, R. (2015). Basic statistics for distributional
symbolic variables: A new metric-based approach.
\emph{Advances in Data Analysis and Classification}, 9(2), 143--175.

Original data from the HistDAWass R package (\code{Agronomique} dataset).
}
\keyword{agriculture}
\keyword{datasets}
\keyword{economics}
\keyword{histogram}
