R: Pollution dataset from McDonald and Schwing (1973)

mcdonald {bestglm} | R Documentation

## Pollution dataset from McDonald and Schwing (1973)

### Description

Regression data used to illustrate ridge regression

### Usage

    data("mcdonald")

### Format

A data frame with 60 observations on the following 16 variables.

`PREC`

  Average annual precipitation in inches

`JANT`

  Average January temperature in degrees F

`JULT`

  Same for July

`OVR65`

  Percent of 1960 SMSA population aged 65 or older

`POPN`

  Average household size

`EDUC`

  Median school years completed by those over 22

`HOUS`

  Percent of housing units which are sound & with all facilities

`DENS`

  Population per sq. mile in urbanized areas, 1960

`NONW`

  Percent non-white population in urbanized areas, 1960

`WWDRK`

  Percent employed in white collar occupations

`POOR`

  Percent of families with income < $3000

`HC`

  Relative hydrocarbon pollution potential

`NOX`

  Same for nitric oxides

`SOx`

  Same for sulphur dioxide

`HUMID`

  Annual average percent relative humidity at 1pm

`MORT`

  Total age-adjusted mortality rate per 100,000

### Details

Ridge regression example

### Source

Gary C. McDonald and Richard C. Schwing (1973), Instabilities of Regression Estimates Relating Air Pollution to Mortality, Technometrics 15/3, 463-481.

### Examples

    data(mcdonald)
    vifx(mcdonald[, -ncol(mcdonald)])

[Package bestglm version 0.36 Index]