eire {spdep} | R Documentation |
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.
data(eire)
This data frame contains the following columns:
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: http://geog-www.sbs.ohio-state.edu/faculty/tiefelsdorf/GeoStat.htm.
data(eire) summary(eire.df$A) brks <- round(fivenum(eire.df$A), digits=2) cols <- rev(heat.colors(4)) library(maptools) plot(eire.polys.utm, col=cols[findInterval(eire.df$A, brks)], forcefill=FALSE) title(main="Percentage with blood group A in Eire") legend(x=c(-50, 70), y=c(6120, 6050), leglabs(brks), fill=cols, bty="n") plot(eire.polys.utm, forcefill=FALSE) plot(eire.nb, eire.coords.utm, add=TRUE) lA <- lag.listw(nb2listw(eire.nb), eire.df$A) summary(lA) moran.test(spNamedVec("A", eire.df), nb2listw(eire.nb)) geary.test(spNamedVec("A", eire.df), nb2listw(eire.nb)) cor(lA, eire.df$A) moran.plot(spNamedVec("A", eire.df), nb2listw(eire.nb), labels=rownames(eire.df)) A.lm <- lm(A ~ towns + pale, data=eire.df) summary(A.lm) res <- residuals(A.lm) brks <- c(min(res),-2,-1,0,1,2,max(res)) cols <- rev(cm.colors(6)) plot(eire.polys.utm, col=cols[findInterval(res, brks)], forcefill=FALSE) title(main="Regression residuals") legend(x=c(-50, 70), y=c(6120, 6050), legend=leglabs(brks), fill=cols, bty="n") lm.morantest(A.lm, nb2listw(eire.nb)) lm.morantest.sad(A.lm, nb2listw(eire.nb)) lm.LMtests(A.lm, nb2listw(eire.nb), test="LMerr") brks <- round(fivenum(eire.df$OWNCONS), digits=2) cols <- grey(4:1/5) plot(eire.polys.utm, col=cols[findInterval(eire.df$OWNCONS, brks)], forcefill=FALSE) 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(spNamedVec("OWNCONS", eire.df), nb2listw(eire.nb)) moran.test(spNamedVec("OWNCONS", eire.df), nb2listw(eire.nb)) e.lm <- lm(OWNCONS ~ ROADACC, data=eire.df) res <- residuals(e.lm) brks <- c(min(res),-2,-1,0,1,2,max(res)) cols <- rev(cm.colors(6)) plot(eire.polys.utm, col=cols[findInterval(res, brks)], forcefill=FALSE) 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:nrow(eire.df)))