bestglm (version 0.37.3)

manpower: Hospital manpower data

Description

The goal of this study is to predict the manpower requirement as given in the output variable Hours given the five other input variables. Data is from Table 3.8 of Myers (1990). See also Examples 3.8, 4.5, 8.8.

Usage

data(manpower)

Format

A data frame with 17 observations. The output variable is Hours and the inputs are Load, Xray, BedDays, AreaPop and Stay. The site 1 through 17 is indicated by the row name.

Load

a numeric vector

Xray

a numeric vector

BedDays

a numeric vector

AreaPop

a numeric vector

Stay

a numeric vector

Hours

a numeric vector

Details

This data illustrates the multicollinearity problem and the use of VIF to identify it. It provides an illustrative example for ridge regression and more modern methods such as lasso and lars.

References

Myers, R. (1990). Classical and Modern Regression with Applications. The Duxbury Advanced Series in Statistics and Decision Sciences. Boston: PWS-KENT Publishing Company.

Examples

# NOT RUN {
data(manpower)
# }