wagnerGrowth {robustbase} | R Documentation |
Wagner's Hannover Employment Growth Data
Description
Wagner (1994) investigates the rate of employment growth (y
) as
function of percentage of people engaged in producation
activities (PA
) and higher services
(HS
) and of the growth of these percentages (GPA
,
GHS
) during three time periods in 21 geographical regions of
the greater Hannover area.
Usage
data(wagnerGrowth, package="robustbase")
Format
A data frame with 21 \times 3 = 63
observations
(one per Region x Period
) on the following 7 variables.
Region
a
factor
with 21 levels, denoting the corresponding region in Hannover (conceptually a “block factor”).PA
numeric: percent of people involved in production activities.
GPA
growth of
PA
.HS
a numeric vector
GHS
a numeric vector
y
a numeric vector
Period
a
factor
with levels1:3
, denoting the time period, 1 = 1979-1982, 2 = 1983-1988, 3 = 1989-1992.
Source
Hubert, M. and Rousseeuw, P. J. (1997). Robust regression with both continuous and binary regressors, Journal of Statistical Planning and Inference 57, 153–163.
References
Wagner J. (1994). Regionale Beschäftigungsdynamik und höherwertige Produktionsdienste: Ergebnisse für den Grossraum Hannover (1979-1992). Raumforschung und Raumordnung 52, 146–150.
Examples
data(wagnerGrowth)
## maybe
str(wagnerGrowth)
require(lattice)
(xyplot(y ~ Period | Region, data = wagnerGrowth,
main = "wagnerGrowth: 21 regions @ Hannover"))
(dotplot(y ~ reorder(Region,y,median), data = wagnerGrowth,
main = "wagnerGrowth",
xlab = "Region [ordered by median(y | Region) ]"))