spdep (version 0.4-9)

eire: Eire data sets

Description

The Eire data set has been converted to shapefile format and placed in the etc/shapes directory. The initial data objects are now stored as a SpatialPolygonsDataFrame object, from which the contiguity neighbour list is recreated. For purposes of record, the original data set is retained.

The eire.df data frame has 26 rows and 9 columns. In addition, polygons of the 26 counties are provided as a multipart polylist in eire.polys.utm (coordinates in km, projection UTM zone 30). Their centroids are in eire.coords.utm. The original Cliff and Ord binary contiguities are in eire.nb.

Usage

data(eire)

encoding

latin1

source

Upton and Fingleton 1985, - Bailey and Gatrell 1995, ch. 1 for blood group data, Cliff and Ord (1973), p. 107 for remaining variables (also after O'Sullivan, 1968). Polygon borders and Irish data sourced from Michael Tiefelsdorf's SPSS Saddlepoint bundle, originally hosted at: http://geog-www.sbs.ohio-state.edu/faculty/tiefelsdorf/GeoStat.htm.

Examples

eire <- readShapePoly(system.file("etc/shapes/eire.shp", package="spdep")[1],
  ID="names", proj4string=CRS("+proj=utm +zone=30 +units=km"))
eire.nb <- poly2nb(eire)
#data(eire)
summary(eire$A)
brks <- round(fivenum(eire$A), digits=2)
cols <- rev(heat.colors(4))
plot(eire, col=cols[findInterval(eire$A, brks, all.inside=TRUE)])
title(main="Percentage with blood group A in Eire")
legend(x=c(-50, 70), y=c(6120, 6050), leglabs(brks), fill=cols, bty="n")
plot(eire)
plot(eire.nb, coordinates(eire), add=TRUE)
lA <- lag.listw(nb2listw(eire.nb), eire$A)
summary(lA)
moran.test(eire$A, nb2listw(eire.nb))
geary.test(eire$A, nb2listw(eire.nb))
cor(lA, eire$A)
moran.plot(eire$A, nb2listw(eire.nb),
 labels=eire$names)
A.lm <- lm(A ~ towns + pale, data=eire)
summary(A.lm)
res <- residuals(A.lm)
brks <- c(min(res),-2,-1,0,1,2,max(res))
cols <- rev(cm.colors(6))
plot(eire, col=cols[findInterval(res, brks, all.inside=TRUE)])
title(main="Regression residuals")
legend(x=c(-50, 70), y=c(6120, 6050), legend=leglabs(brks), fill=cols,
  bty="n")
lm.morantest(A.lm, nb2listw(eire.nb))
lm.morantest.sad(A.lm, nb2listw(eire.nb))
lm.LMtests(A.lm, nb2listw(eire.nb), test="LMerr")brks <- round(fivenum(eire$OWNCONS), digits=2)
cols <- grey(4:1/5)
plot(eire, col=cols[findInterval(eire$OWNCONS, brks, all.inside=TRUE)])
title(main="Percentage own consumption of agricultural produce")
legend(x=c(-50, 70), y=c(6120, 6050), legend=leglabs(brks),
  fill=cols, bty="n")
moran.plot(eire$OWNCONS, nb2listw(eire.nb))
moran.test(eire$OWNCONS, nb2listw(eire.nb))
e.lm <- lm(OWNCONS ~ ROADACC, data=eire)
res <- residuals(e.lm)
brks <- c(min(res),-2,-1,0,1,2,max(res))
cols <- rev(cm.colors(6))
plot(eire, col=cols[findInterval(res, brks, all.inside=TRUE)])
title(main="Regression residuals")
legend(x=c(-50, 70), y=c(6120, 6050), legend=leglabs(brks), fill=cm.colors(6),
  bty="n")
lm.morantest(e.lm, nb2listw(eire.nb))
lm.morantest.sad(e.lm, nb2listw(eire.nb))
lm.LMtests(e.lm, nb2listw(eire.nb), test="LMerr")
print(localmoran.sad(e.lm, eire.nb, select=1:length(slot(eire, "polygons"))))