Learn R Programming

spdep (version 0.2-3)

nc.sids: North Carolina SIDS data

Description

The nc.sids data frame has 100 rows and 9 columns. It contains data given in Cressie (1991, pp. 386-9), Cressie and Read (1985) and Cressie and Chan (1989) on sudden infant deaths in North Carolina for 1974-78 and 1979-84. The data set also contains the neighbour list given by Cressie and Chan (1989) omitting self-neighbours (ncCC89.nb), and the neighbour list given by Cressie and Read (1985) for contiguities (ncCR85.nb).

Usage

data(nc.sids)

Arguments

source

Cressie, N (1991), Statistics for spatial data. New York: Wiley, pp. 386--389; Cressie, N, Chan NH (1989) Spatial modelling of regional variables. Journal of the American Statistical Association, 84, 393--401; Cressie, N, Read, TRC (1985) Do sudden infant deaths come in clusters? Statistics and Decisions Supplement Issue 2, 333--349; http://sal.agecon.uiuc.edu/datasets/sids.zip.

Examples

Run this code
library(maptools)
sids.shp <- read.shape(system.file("shapes/sids.shp",
 package="maptools"))
sids <- sids.shp$att.data
sidspolys <- Map2poly(sids.shp)
sidscents <- get.Pcent(sids.shp)
data(nc.sids)
sids[1:5, c("CNTY.ID", "NAME", "BIR74")]
nc.sids[1:5, c("CNTY.ID", "BIR74")]
attr(ncCC89.nb, "region.id")[1:5]
tmpGAL <- tempfile(pattern="GAL")
write.nb.gal(ncCC89.nb, file=tmpGAL, oldstyle=FALSE, 
 shpfile="sids", ind="CNTY.ID")
CNTY.ID <- sids$CNTY.ID
ncCC89.2.nb <- read.gal(file=tmpGAL, region.id=CNTY.ID)
tmpGAL <- tempfile(pattern="GAL")
write.nb.gal(ncCR85.nb, file=tmpGAL, oldstyle=FALSE, 
 shpfile="sids", ind="CNTY.ID")
CNTY.ID <- sids$CNTY.ID
ncCR85.2.nb <- read.gal(file=tmpGAL, region.id=CNTY.ID)
plotpolys(sidspolys, border="grey")
plot(ncCR85.2.nb, sidscents, add=TRUE, col="blue")
plotpolys(sidspolys, border="grey")
plot(ncCC89.2.nb, cbind(nc.sids$lon, nc.sids$lat)[order(nc.sids$CNTY.ID),],
 add=TRUE, col="blue")

Run the code above in your browser using DataLab