A data frame with 366 observations on 13 variables, each
observation is one day
Usage
data(Ozone)
Format
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
Details
The problem is to predict the daily maximum one-hour-average
ozone reading (V4).
Source
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.