On Fri, 25 Jun 2010, Julien Beguin wrote:
Dear list member,
I am using the autocov_dist function in spdep on binary point data set
to estimate the autocovariate to be used in autologistic regression
(session info at the end):
coords<-as.matrix(cbind(datafile$X_COORD, datafile$Y_COORD))
ac1 <- autocov_dist(datafile$binary_variable, coords, nbs=400, type =
"inverse", zero.policy=TRUE)
It works fine with large value of nbs. When nbs value is below the neibhorhood
distance of some pairs of point I get warnings because of empty neighbors:
Warning messages: 1: In autocov_dist(datafile$binary_variable, coords,
nbs = 400, type = "inverse", :
With value 400 some points have no neighbours
2: In nb2listw(nb, glist = gl, style = style, zero.policy = zero.policy) :
zero sum general weights
It seems, but I might be wrong, that points with no neighbour have an
autocov_dist value of zero. Since it is what I want, it is ok for me.
No, the general weights sum to zero, as it says, you are using inverse.
But if I decrease nbs value below the smallest neighbourhood distance
among pairs of points in my data set, I get an error message:
Error in nb2listw(nb, glist = gl, style = style, zero.policy = zero.policy) :
No valid observations
In addition: Warning messages:
1: In autocov_dist(datafile$binary_variable, coords, nbs = 100, type =
"inverse", :
With value 100 some points have no neighbours
2: In nb2listw(nb, glist = gl, style = style, zero.policy = zero.policy) :
zero sum general weights
My question is as follows: why do autocov_dist function require that at
least one neighbor pair exists? and why not returning zero value for all
points when no any point has a neighbor?
This might appear to be a strange question but in my case I estimating
autocov_dist for different spatial block in which the minimum distance
between points vary from block to block, but still I would like a commun
nbs value for all block.
It does indeed seem very strange, as you are asking to include a constant
vector of zeros, which will alias the constant. The function itself is a
really bad idea, and is included only to show (see Dormann et al 2007)
that using it is inferior to all other methods examined there. Trying to
include a second zero constant doesn't seem well-founded, to put it
mildly.
Hope this helps,
Roger
Thank you for your help,
Julien Beguin
--------------------
Ph.D. student
Laval University
Québec, Canada
SESSION INFO:
R version 2.10.1 (2009-12-14)
i386-pc-mingw32
locale:
[1] LC_COLLATE=French_Canada.1252 LC_CTYPE=French_Canada.1252
[3] LC_MONETARY=French_Canada.1252 LC_NUMERIC=C
[5] LC_TIME=French_Canada.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] spdep_0.5-4 spam_0.20-3 coda_0.13-4
[4] deldir_0.0-12 maptools_0.7-29 foreign_0.8-40
[7] nlme_3.1-96 MASS_7.3-4 Matrix_0.999375-33
[10] lattice_0.17-26 boot_1.2-41 sp_0.9-60
[13] compositions_1.01-1 robustbase_0.5-0-1 tensorA_0.31
[16] rgl_0.91
loaded via a namespace (and not attached):
[1] grid_2.10.1 tools_2.10.1
_______________________________________________
R-sig-Geo mailing list
R-sig-Geo@stat.math.ethz.ch
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
--
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: roger.biv...@nhh.no
_______________________________________________
R-sig-Geo mailing list
R-sig-Geo@stat.math.ethz.ch
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
