| Ozone {e1071} | R Documentation |
A data frame with 366 observations on 13 variables, each observation is one day
data(Ozone)
| 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 |
The problem is to predict the daily maximum one-hour-average ozone reading (V4).
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.