On Tue, 3 Apr 2012, dwl Al_Sulami wrote:
Dear there
I am trying to construct spatial weight matrix using inverse distance, which
means that high weight is given to near observations and ,vies versa, where
w_ij=w_ji and w_ii=0, Since, I am a new R user, I've tried many functions in
sp,spdep packages and I find some functions to find weight matrix by using
nearest neighbours and by distance-based neighbours, but I want to use all
observations as neighbours and based on the inverse distance, I can construct
the weights.
Before I write the code I'll give some information about my data, I have the
coordinates of 51 states (US states) , thus latitude and longitude of each
states and based on the distance between each state I will give a weight for
states where the weight is the the inverse of the distance. obviously , the
weight matrix are symmetric.
Then I've tried the following code
data(location)# data.frame with 2 col and 51 row
loc.sp = SpatialPoints(cbind(location$latitude,location$longitude))
sy8<-knn2nb(knearneigh(loc.sp,k=50)) # for each state all other states are
considered as neighbour
dsts<-nbdists(sy8, loc.sp)
idw<-lapply(dsts, function(x) 1/(x))
sy<-nb2listw(sy8, glist=idw, style="B")
col.mat <- listw2mat(sy)
after running this code, I got symmetric matrix (51* 51), where w_ii=0 and
w_ij=w_ji
but I am not sure if this is true!!!
What do you mean by true - correct? There is at least one problem, that
you are not ensuring that the distances are computed by Great Circle. More
or less reproducing your code (data(locations) must be wrong):
library(maps)
sts <- map("state", fill=TRUE, plot=FALSE)
library(maptools)
IDs <- sapply(strsplit(sts$names, ":"), function(x) x[1])
SPl <- map2SpatialPolygons(sts, IDs=IDs,
proj4string=CRS("+proj=longlat +datum=WGS84"))
crds <- SpatialPoints(coordinates(SPl),
proj4string=CRS("+proj=longlat +datum=WGS84"))
is.projected(crds)
library(spdep)
nbs <- dnearneigh(crds, 0, 10000)
# either crds a SpatialPoints object !is.projected(), or use longlat=TRUE
nbs
dsts <- nbdists(nbs, crds)
# either crds a SpatialPoints object !is.projected(), or use longlat=TRUE
summary(unlist(dsts))
# in km
idw <- lapply(dsts, function(x) 1/(x))
sy <- nb2listw(nbs, glist=idw, style="B")
col.mat <- listw2mat(sy)
all.equal(col.mat, t(col.mat), check.attributes=FALSE)
I think that your "distances" were planar measures in geographical
coordinates.
Hope this helps,
Roger
any commands and helps are appreciated
Regards,
Alsulami
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Roger Bivand
Department of Economics, NHH Norwegian School of Economics,
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e-mail: roger.biv...@nhh.no
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