% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{ozone.hist}
\alias{ozone.hist}
\title{Ozone Air Quality Histogram-Valued Dataset}
\format{
A data frame with 84 observations (days) and 4 histogram-valued
variables:
\itemize{
    \item \code{Ozone.Conc.ppb}: Histogram of ozone concentration (ppb).
    \item \code{Temperature.C}: Histogram of temperature (Celsius).
    \item \code{Solar.Radiation.WattM2}: Histogram of solar radiation (W/m^2).
    \item \code{Wind.Speed.mSec}: Histogram of wind speed (m/s).
}
Row names are I1 through I84.
}
\source{
HistDAWass R package (\code{OzoneH} dataset).
}
\usage{
data(ozone.hist)
}
\description{
Histogram-valued dataset of 84 daily observations with 4 weather-related
histogram variables. Each histogram has 10 equal-probability (decile) bins
summarizing hourly measurements within each day.
}
\section{Metadata}{

\tabular{ll}{
  \strong{Sample size (n)} \tab 84 \cr
  \strong{Variables (p)} \tab 4 \cr
  \strong{Subject area} \tab Environment \cr
  \strong{Symbolic format} \tab Histogram \cr
  \strong{Analytical tasks} \tab Regression, Clustering
}
}

\examples{
data(ozone.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{OzoneH} dataset),
reduced from 100 quantile bins to 10 decile bins.
}
\keyword{datasets}
\keyword{environment}
\keyword{histogram}
\keyword{weather}
