globalG.test - routine with distance based neighbours
On Fri, 5 Feb 2016, Francesco Perugini wrote:
Dear Prof. Bivand, thanks a lot for the reply. sure, it should be c(0.620, 0.650, 0.700). sorry but "There is no dnb[[620]], it is length(dnb) == length(z) long", is
You cannot use (val in z) to index dnb, which takes the integers 1:3 only. Previously, your k was an integer sequence. Roger
not clear to me. Many thanks. Regards. franc.per 2016-02-05 13:27 GMT+01:00 Roger Bivand <Roger.Bivand at nhh.no>:
On Fri, 5 Feb 2016, Francesco Perugini wrote: Dear all,
I've routine that plot Glogal G statistics at different k-neighbours. I've tried to run it using distance based neighbours method but I got this message: Error in dnb[[val]] : subscript out of bounds
val is defined in for (val in z), and z in z <- c(620, 650, 700) - arguably should be c(0.620, 0.650, 0.700) given all.linkedT as 0.619. There is no dnb[[620]], it is length(dnb) == length(z) long. Roger
Any suggestion on this? Thanks a lot. franc.per
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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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-- Roger Bivand Department of Economics, Norwegian School of Economics, Helleveien 30, N-5045 Bergen, Norway. voice: +47 55 95 93 55; fax +47 55 95 91 00 e-mail: Roger.Bivand at nhh.no http://orcid.org/0000-0003-2392-6140 https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en http://depsy.org/person/434412
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Roger Bivand Department of Economics, Norwegian School of Economics, Helleveien 30, N-5045 Bergen, Norway. voice: +47 55 95 93 55; fax +47 55 95 91 00 e-mail: Roger.Bivand at nhh.no http://orcid.org/0000-0003-2392-6140 https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en http://depsy.org/person/434412