datozone: datozone

In mlesnoff/rnirs: Dimension reduction, Regression and Discrimination for Chemometrics

datozone

Description

Los Angeles ozone pollution data in 1976 (sources: Breiman & Friedman 1985, Leisch & Dimitriadou 2020).

366 observations, 13 variables:

- 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 (

- 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 variable to predict is V4.

Usage

data(datozone)

Format

A list with 1 component: matrix X.

Source

Breiman L., Friedman J.H. 1985. Estimating optimal transformations for multiple regression and correlation, JASA, 80, pp. 580-598.

Leisch, F. and Dimitriadou, E. (2010). mlbench: Machine Learning Benchmark Problems. R package version 1.1-6. https://cran.r-project.org

Examples

data(datozone)

z <- datozone$X
head(z)

plotxna(z)

mlesnoff/rnirs documentation built on April 24, 2023, 4:17 a.m.