\HeaderA{Ozone}{Los Angeles ozone pollution data, 1976}{Ozone}
\keyword{datasets}{Ozone}
\begin{Description}\relax
A data frame with 366 observations on 13 variables, each
observation is one day
\end{Description}
\begin{Usage}
\begin{verbatim}data(Ozone)\end{verbatim}
\end{Usage}
\begin{Format}\relax
\Tabular{rl}{
1 & Month: 1 = January, ..., 12 = December\\
2 & Day of month\\
3 & Day of week: 1 = Monday, ..., 7 = Sunday\\
4 & Daily maximum one-hour-average ozone reading\\
5 & 500 millibar pressure height (m) measured at Vandenberg AFB\\
6 & Wind speed (mph) at Los Angeles International Airport (LAX)\\
7 & Humidity (\%) at LAX\\
8 & Temperature (degrees F) measured at Sandburg, CA\\
9 & Temperature (degrees F) measured at El Monte, CA\\
10 & Inversion base height (feet) at LAX\\
11 & Pressure gradient (mm Hg) from LAX to Daggett, CA\\
12 & Inversion base temperature (degrees F) at LAX\\
13 & Visibility (miles) measured at LAX\\
}
\end{Format}
\begin{Details}\relax
The problem is to predict the daily maximum one-hour-average
ozone reading (V4).
\end{Details}
\begin{Source}\relax
Leo Breiman, Department of Statistics, UC Berkeley.  Data used in
Leo Breiman and Jerome H. Friedman (1985), Estimating optimal
transformations for multiple regression and correlation, JASA, 80, pp.
580-598.
\end{Source}

