| whittermore.stat {DCluster} | R Documentation |
Compute Whittermore's statistic. See whittermore manual page for more details.
whittermore.stat(data, listw, zero.policy=FALSE)
data |
Dataframe with the data, as desribed in DCluster manual page. |
listw |
Neighbours list with spatial weights created, for example, by 'nb2listw' (package spdep). |
zero.policy |
See nb2listw in package spdep. |
The value of the statistic.
Whittermore, A. S. and Friend, N. and Byron, W. and Brown, J. R. and Holly, E. A. (1987). A test to detect clusters of disease. Biometrika 74, 631-635.
DCluster, whittermore, whittermore.boot, whittermore.pboot
library(spdep)
data(nc.sids)
col.W <- nb2listw(ncCR85.nb, zero.policy=TRUE)
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)
#Calculate neighbours based on distance
coords<-as.matrix(sids[,c("x", "y")])
dlist<-dnearneigh(coords, 0, Inf)
dlist<-include.self(dlist)
dlist.d<-nbdists(dlist, coords)
#Calculate weights. They are globally standardised but it doesn't
#change significance.
col.W.whitt<-nb2listw(dlist, glist=dlist.d, style="C")
whittermore.stat(sids, col.W.whitt, zero.policy=TRUE)