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)])