_______________
this is the routine
library(spdep)
example(columbus)
coord <- coordinates(columbus)
#k-nearest neighbours
#z <- c(1:20)
#neighbors.knn <- list()
#Distance-based neighbours
k1 <- knn2nb(knearneigh(coord,k=1,longlat=F))
all.linkedT <- max(unlist(nbdists(k1, coord,longlat=F)))
all.linkedT
z <- c(620, 650, 700)
dnb <- list()
for (val in z)
{
dnb <- c(dnb, list(dnearneigh(coord, 0, val, longlat=F)))
# neighbors.knn <- c(neighbors.knn, list(knn2nb(knearneigh(coord, val,
longlat=F), sym=F)))
}
list(dnb)
ndists <- length(z)
ZG <- vector(mode="list", length=ndists)
names(ZG) <- as.character(z)
f <- c("CRIME", "INC")
for (val in z)
{
# dlwknn.B <- nb2listw(neighbors.knn[[val]], style="B", zero.policy=TRUE)
dlwdnb.B <- nb2listw(dnb[[val]], style="B", zero.policy=TRUE)
temp <- list()
for (var in f)
{
# temp <- c(temp, list(globalG.test(columbus[[var]], dlwknn.B,
zero.policy=F)))
temp <- c(temp, list(globalG.test(columbus[[var]], dlwdnb.B,
zero.policy=F)))
}
ZG[[val]] <- temp
}
t(sapply(lapply(ZG, "[[", 1), function(var) c(var$estimate[1],
var$statistic,
p.value=unname(var$p.value))))
CRIME <- t(sapply(lapply(ZG, "[[", 1), function(var) c(var$estimate[1],
var$statistic,
p.value=unname(var$p.value))))
plot(z, CRIME[,1], xlab="distance", ylab="Global G", xlim=NULL,
axes=TRUE, type="o", col="blue")
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