help in constructing spatial weight matrix

Dear list,

Given a following up to this question, I have myself a somewhat similar
question to that of Alsulami.
I have a shp of Finnish cities and would like to generate for them a weight
matrix of neighborhood based on inverse distance (for further use in
Moran's I calculus). Here is the code I've been thinking of:


 UF.shp <- readShapePoly(myshpfile.shp, IDvar="OBJECTID")
 UF.nb <- poly2nb(UF.shp, queen=TRUE)
 dsts <- nbdists(UF.nb, coordinates(UF.shp))
 idw <- lapply(dsts, function(x) 1/(x/1000))
 UF.listw <- nb2listw(UF.nb, glist = idw, style="B", zero.policy=TRUE)


But it does not work and I can't figure how to fully adapt the idea to the
shp I have.
Anyone please could give me any tips?

Best,

FABRICIO




2012/4/3 Roger Bivand <Roger.Bivand at nhh.no>

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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voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: Roger.Bivand at nhh.no