[R-sig-Geo] globalG.test - routine with distance based neighbours

Francesco Perugini francescoperugini07 at gmail.com
Fri Feb 5 16:42:37 CET 2016


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
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
>>
>> _______________
>>
>> 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")
>>
>>         [[alternative HTML version deleted]]
>>
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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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