[RsigGeo] inverse distance weights matrix
Griffin, Terry W
twgriffi at purdue.edu
Tue Apr 11 15:56:13 CEST 2006
Thanks Roger,
I've been working on creating inverse distance matrices; and have been
successful in this first step. However, as you suggested, the
connectedness of these matrices will cause procedures to be slow, even
prohibitive with my computer (P4 3Gz 1GB RAM) (ran out of RAM).
I've tried a simpler first order queen weights matrix to see if I could
get the errorsarlm model to run; but come to a different problem and an
error message:
source("spat.cot.R")
Error in solve.default(asyvar, tol = tol.solve) :
system is computationally singular: reciprocal condition number
= 1.16119e019
> traceback()
6: solve.default(asyvar, tol = tol.solve)
5: solve(asyvar, tol = tol.solve)
4: errorsarlm(YLD02 ~ CLAY + DIST + PEG + ROT + SUN, data = cotton,
q1)
3: eval.with.vis(expr, envir, enclos)
2: eval.with.vis(ei, envir)
1: source("spat.cot.R")
where "spat.cot.R" contains:
spatcot.err<errorsarlm(YLD02~CLAY+DIST+PEG+ROT+SUN,data=cotton, q1)
Do I need to set my tol to a different value or am I having other
issues?
Thank you,
Terry
Original Message
From: Roger Bivand [mailto:Roger.Bivand at nhh.no]
Sent: Saturday, March 18, 2006 3:07 PM
To: Griffin, Terry W
Cc: rsiggeo at stat.math.ethz.ch
Subject: RE: [RsigGeo] inverse distance weights matrix
On Sat, 18 Mar 2006, Griffin, Terry W wrote:
> Thank you Roger,
>
> I've posted the original shape file for the dataset on the website at:
> http://web.ics.purdue.edu/~twgriffi/R_matrix.htm
>
> One shape file is projected while the other is not; however both sets
of
> *.dbf are identical and contain both decimal degrees and Northing and
> Easting in meters.
>
> I chose a <=75 meter distance threshold and a power=1.
>
> The final inverse distance matrix was row standardized so it is not
> symmetric. The weight characteristics you list below are nearly
> identical to those that SpaceStat provides.
OK  it looks like this at the moment:
library(rgdal)
cotton_proj < readOGR(".", "cotton_proj") # for shapefiles in the
current
# working directory, first argument
plot(cotton_proj, cex=0.2, axes=TRUE)
library(spdep)
d75 < dnearneigh(coordinates(cotton_proj), 0, 75)
dlist < nbdists(d75, coordinates(cotton_proj))
idlist < lapply(dlist, function(x) 1/x)
w75 < nb2listw(d75, glist=idlist, style="W")
Characteristics of d75:
> d75
Neighbour list object:
Number of regions: 2451
Number of nonzero links: 1182994
Percentage nonzero weights: 19.69228
Average number of links: 482.6577
But:
> inMAT < matrix(scan("cottonID75wm", sep=","), nrow=2451, ncol=2451,
+ byrow=TRUE)
> range(rowSums(inMAT))
[1] 0.8159028 1.9115231
> d75MAT < nb2mat(d75, glist=idlist, style="W")
> range(rowSums(d75MAT))
[1] 1 1
> w75 < nb2listw(d75, glist=idlist, style="W")
> range(sapply(w75$weights, sum))
[1] 1 1
So something in the construction of your matrix wasn't securing row
standardisation. The values do differ, this is the upper left corner:
> d75MAT[1:5,1:5]
[,1] [,2] [,3] [,4] [,5]
1 0.00000000 0.06735710 0.03227068 0.02182278 0.01660474
2 0.05975093 0.00000000 0.05493976 0.02863058 0.01954588
3 0.02615210 0.05019078 0.00000000 0.05461937 0.02771729
4 0.01639324 0.02424508 0.05062943 0.00000000 0.05216365
5 0.01172946 0.01556467 0.02416008 0.04905229 0.00000000
> inMAT[1:5,1:5]
[,1] [,2] [,3] [,4] [,5]
[1,] 0.000000 0.131420 0.061844 0.041726 0.031848
[2,] 0.101440 0.000000 0.090156 0.047180 0.032441
[3,] 0.040305 0.076122 0.000000 0.083545 0.042787
[4,] 0.023708 0.034730 0.072836 0.000000 0.076431
[5,] 0.016296 0.021506 0.033593 0.068830 0.000000
> rowSums(inMAT[1:5,])
[1] 1.911523 1.658689 1.533153 1.440908 1.379051
> rowSums(d75MAT[1:5,])
1 2 3 4 5
1 1 1 1 1
They are not the same matrices, although the differences are very small

here I've used the shapefile points, which are stored as binary floating
point, rather than using the DBF values, which are a possibly rounded
character representation, and that might be enough to cause the
difference. I think you should be able to generate w75, and that it
should
do what you need, but I'd be grateful for feedback on how you get on.
Best wishes,
Roger
PS: with numbers of neighbours between 177 and 678 (both in your matrix
and in d75), even allowing for the dampening effect of inverse distance,
most analyses will be slow. 75m means that many sites are related to
many
in your case. Doing:
symbols(408725, 3660800, circles=75, inches=FALSE, fg="red", add=TRUE)
on top of the earlier plot shows your chosen neighbourhood for an
arbitrary point.
>
> I really appreciate this. Thank you,
>
> Terry
>
>
>
> Original Message
> From: Roger Bivand [mailto:Roger.Bivand at nhh.no]
> Sent: Friday, March 17, 2006 5:50 PM
> To: Griffin, Terry W
> Cc: rsiggeo at stat.math.ethz.ch
> Subject: RE: [RsigGeo] inverse distance weights matrix
>
> Terry:
>
> http://web.ics.purdue.edu/~twgriffi/mat4rf
>
> and
>
> http://web.ics.purdue.edu/~twgriffi/mat4rs
>
> throw access errors.
>
> Do you have the coordinates and your specifications for the inverse
> weighted neighbours (distance threshold, power if any)?
>
> inMAT < matrix(scan("cottonID75wm", sep=","), nrow=2451, ncol=2451,
> byrow=TRUE)
>
> does read the matrix  the weights aren't symmetric, are they?
>
> From the weights matrix I get:
>
> inMATlw < mat2listw(inMAT)
>
> print(is.symmetric.nb(inMATlw$neighbours))
> [1] TRUE
>
> print(inMATlw$neighbours)
> Neighbour list object:
> Number of regions: 2451
> Number of nonzero links: 1182982
> Percentage nonzero weights: 19.69208
> Average number of links: 482.6528
>
> If you could post the coordinates and your specifications, I could see
> how
> to reproduce the weights within R if you like.
>
> Roger
>
>
> On Fri, 17 Mar 2006, Griffin, Terry W wrote:
>
> >
> > The MATLAB routines are the Spatial Econometrics Toolbox format. I
> > tried the read.dat2listw() in R; the code and error message for a
> small
> > matrix example is below; this uses a full matrix from MATLAB
> (realizing
> > that "read.dat2listw" is intended for sparse matrices).
> >
> > > mattry<read.dat2listw("mat4rf")
> > Error in "[.default"(sn, , 1) : incorrect number of dimensions
> > > traceback()
> > 5: NextMethod("[")
> > 4: "[.factor"(sn, , 1)
> > 3: sn[, 1]
> > 2: unique(sn[, 1])
> > 1: read.dat2listw("mat4rf")
> >
> >
> > I'm not able to use dlmwrite in MATLAB to export the sparse matrix
so
> I
> > tried to import the full matrix into R (code is above). The MATLAB
> code
> > I'm using came from this listserve archive. The MATLAB code and
error
> > message are below. I'm able to use dlmwrite to create the MATLAB
full
> > matrix (used above in the R code).
> >
> > load testmat.GWT; A = (spconvert(testmat)); %have to change name in
> two
> > locations on this line
> > n=size(A); nobs=n(1);
> > % Normalize matrix (adapted form LeSage 1999)
> > wt = sparse(A);
> > [i1,j1,s1]=find(wt);
> > rsum=sum(wt);
> > for i=1:nobs;
> > ind=find(i1==i);
> > s1(ind,1)=s1(ind,1)/rsum(1,i);
> > end;
> > [m,n] = size(wt);
> > W = sparse(i1,j1,s1,m,n);
> > S = sparse(W);
> > dlmwrite('mat4rst', S); %give the new sparse weight matrix a
permanent
> > name for R
> > ??? Error using ==> sprintf
> > Function is not defined for sparse inputs.
> >
> > Error in ==> dlmwrite at 172
> > str = sprintf(format,m(i,:));
> >
> > If anyone wants to give it a try, I've put the small example
matrices
> > and the "real" matrix up on my website at:
> > http://web.ics.purdue.edu/~twgriffi/R_matrix.htm
> >
> > My objective is to use R for my spatial data analysis using inverse
> > distance weights matrices. I'm struggling with the inverse distance
> > matrices. I hope to either create these inverse distance matrices
in
> > SpaceStat then import into R or create the matrices in R.
> >
> > Thank you,
> >
> > Terry
> >
> >
> >
> >
> > Original Message
> > From: Roger Bivand [mailto:Roger.Bivand at nhh.no]
> > Sent: Friday, March 17, 2006 2:43 PM
> > To: Griffin, Terry W
> > Cc: rsiggeo at stat.math.ethz.ch
> > Subject: Re: [RsigGeo] inverse distance weights matrix
> >
> > On Thu, 16 Mar 2006, Griffin, Terry W wrote:
> >
> > > Greetings,
> > >
> > >
> > >
> > > I'm migrating from MATLAB to R and am having trouble converting
> > inverse
> > > distance weights matrix into a form usable by R. I've created the
> > > matrix in SpaceStat (in *.FMT format) and converted to *.GWT
format
> > and
> > > also have it in MATLAB *.m format.
> > >
> >
> > I wonder whether your Matlab data are in the Spatial Econometrics
> > Toolbox
> > format  if they are, you could try the read.dat2listw() function
> > mentioned on the read.gwt2nb function help page.
> > >
> > >
> > > I've tried using the read.gwt2nb in R, but without success. There
> are
> > > nearly 2,451 observations with an average of 482 linkages. About
20
> %
> > > have nonzero weights. Any suggestions are appreciated.
> >
> > Without details of what you mean by "without success", it's hard to
> > offer
> > any advice. Could you create a small example of the problems you are
> > seeing, and repost with copies of the commands you give and any
error
> > messages?
> >
> > If you are seeing errors ("Error in ..." messages from R), please
also
> > type traceback() at the prompt and report the output. You could also
> put
> > the uncooperative GWT file on a website for others to try to see
what
> is
> > going on.
> >
> > >
> > >
> > >
> > > Thank you,
> > >
> > > Terry
> > >
> > >
> > >
> > >
> > >
> > > Terry W. Griffin
> > >
> > > Graduate Research Assistant
> > >
> > > Agricultural Economics
> > >
> > > Purdue University
> > >
> > > 403 W State St
> > >
> > > West Lafayette, IN 47907
> > >
> > > 7654944257
> > >
> > > http://web.ics.purdue.edu/~twgriffi/
> > > <http://web.ics.purdue.edu/~twgriffi/>
> > >
> > >
> > >
> > >
> > >
> > >
> > > [[alternative HTML version deleted]]
> > >
> > > _______________________________________________
> > > RsigGeo mailing list
> > > RsigGeo at stat.math.ethz.ch
> > > https://stat.ethz.ch/mailman/listinfo/rsiggeo
> > >
> >
> >
>
>

Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
email: Roger.Bivand at nhh.no
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