Besag and Newell's Statistic for Spatial Clustering

Description

Besag & Newell's statistic looks for clusters of size k, i. e., where the number of observed cases is k. At every area where a case has appeared, the number of neighbouring regions needed to reach $k$ cases is calculated. If this number is too small, that is, too many observed cases in just a few regions with low expected cases, then it is marked as a cluster.

References

Besag, J. and Newell, J.(1991). The detection of clusters in rare diseases. Journal of the Royal Statistical Society A 154, 143-155.

See Also

DCluster, besagnewell.stat, besagnewell.boot, besagnewell.pboot, bn.iscluster

Examples

#B&N must use the centroids as grid.
#The size of teh cluster is 20.
#100  bootstrap simulations are performed
#Poisson is the model used in the bootstrap simulations to generate the
#observations.
#Signifiance level is 0'05, even though multiple tests are made.

library(boot)
library(spdep)

data(nc.sids)

sids<-data.frame(Observed=nc.sids$SID74)
sids<-cbind(sids, Expected=nc.sids$BIR74*sum(nc.sids$SID74)/sum(nc.sids$BIR74))
sids<-cbind(sids, x=nc.sids$x, y=nc.sids$y)

bnresults<-opgam(sids, thegrid=sids[,c("x","y")], alpha=.05, 
	iscluster=bn.iscluster, set.idxorder=TRUE, k=20, model="poisson", 
	R=100, mle=calculate.mle(sids) )

#Plot all the centroids
plot(sids$x, sids$y)

#Plot signifiant centroids in red
points(bnresults$x, bnresults$y, col="red", pch=19)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(DCluster)
Loading required package: boot
Loading required package: spdep
Loading required package: sp
Loading required package: Matrix
Loading required package: MASS
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/DCluster/besagnewell.Rd_%03d_medium.png", width=480, height=480)
> ### Name: besagnewell
> ### Title: Besag and Newell's Statistic for Spatial Clustering
> ### Aliases: besagnewell
> ### Keywords: spatial
> 
> ### ** Examples
> 
> #B&N must use the centroids as grid.
> #The size of teh cluster is 20.
> #100  bootstrap simulations are performed
> #Poisson is the model used in the bootstrap simulations to generate the
> #observations.
> #Signifiance level is 0'05, even though multiple tests are made.
> 
> library(boot)
> library(spdep)
> 
> data(nc.sids)
> 
> sids<-data.frame(Observed=nc.sids$SID74)
> sids<-cbind(sids, Expected=nc.sids$BIR74*sum(nc.sids$SID74)/sum(nc.sids$BIR74))
> sids<-cbind(sids, x=nc.sids$x, y=nc.sids$y)
> 
> bnresults<-opgam(sids, thegrid=sids[,c("x","y")], alpha=.05, 
+ 	iscluster=bn.iscluster, set.idxorder=TRUE, k=20, model="poisson", 
+ 	R=100, mle=calculate.mle(sids) )
> 
> #Plot all the centroids
> plot(sids$x, sids$y)
> 
> #Plot signifiant centroids in red
> points(bnresults$x, bnresults$y, col="red", pch=19)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>