oops - I meant to say - with row-standardization your weights become:
1/dij/n-1 (with 0 elements on the diagonal).
So, you've just rescaled dij by n-1 for all i, but you haven't lost the
ranking of the distances from low to high.
From: Roger Bivand
To: Jill Caviglia-Harris
Cc: r-sig-geo at stat.math.ethz.ch
Sent: 2/27/04 2:40 PM
Subject: Re: [R-sig-Geo] LM tests
On Fri, 27 Feb 2004, Jill Caviglia-Harris wrote:
> List members:
> I have been using the function lm.LMtests developed using the spdep
> package to test for spatial lag and error. My problem is that these
> tests assume that the weights matrix is row standardized, while I have
> weights matrix that is set up as the inverse distance between
Certainly lm.LMtests() prints a warning, and the tradition it comes from
usually presupposes row standardisation. Curiously, quite a lot of the
distribution results in Cliff and Ord actually assume symmetry, which
lead to fun with negative variance in Geary's C and join count
even with row standardised weights.
> Converting it into a row standardized matrix would result in the
> of important information. Have there been any functions developed
> any of you know about that are not dependent upon this assumption?
Have you tried (probably yes) and does it make a difference? Are the
results from a binary IDW and a row standardised IDW very different? Is
your IDW matrix full or sparse? Can Moran's I be applied instead
its covering lots of misspecification problems)? Are the IDW weights
symmetric (probably, but not always)?
I'm not sure why distances should be helpful if the data are observed on
areal units, so that measuring distances is between arbitrarily chosen
points in those units, a change of support problem. That may be why
aren't methods too, though there's no reason not to try to develop
But error correlation specified by distance does movbe rather close to
geostatistics, doesn't it?
Any other views, anyone?
> Thanks. -Jill
> Jill L. Caviglia-Harris, Ph.D.
> Assistant Professor
> Economics and Finance Department
> Salisbury University
> Salisbury, MD 21801-6860
> phone: (410) 548-5591
> fax: (410) 546-6208
> R-sig-Geo mailing list
> R-sig-Geo at stat.math.ethz.ch
> https://www.stat.math.ethz.ch/mailman/listinfo/r-sig-geo >
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Breiviksveien 40, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 93 93
e-mail: Roger.Bivand at nhh.no