[R-sig-Geo] Choice of Spatial weights

Darla Munroe munroe.9 at osu.edu
Sun Mar 2 22:18:24 CET 2008

Here's another paper that seems to support the idea that when in doubt, go
with a sparser representation:

R.J.G.M. Florax and S.J. Rey, The impacts of misspecified spatial weight
structures in linear regression models. In: L. Anselin and R.J.G.M. Florax,
Editors, New Directions in Spatial Econometrics, Springer Verlag, Berlin

- DM

-----Original Message-----
From: r-sig-geo-bounces at stat.math.ethz.ch
[mailto:r-sig-geo-bounces at stat.math.ethz.ch] On Behalf Of Roger Bivand
Sent: Sunday, March 02, 2008 3:42 PM
To: stefan lhachimi
Cc: r-sig-geo at stat.math.ethz.ch
Subject: Re: [R-sig-Geo] Choice of Spatial weights

On Fri, 29 Feb 2008, stefan lhachimi wrote:

> Dear all,
> as a matter of curiosity does anybody know literature which discusses
> what spatial weight to choose (e.g. k-nn, single or double
> contiguity)? Or has anybod a good rule of thumb?

There are papers by Daniel Griffith, and one by Francois Bavaud, both 
prefer sparse to denser. This one is online:


> I found an article which proposes to try several specification and
> take either the one with the highest lambda  or the one with the best
> overall model fit (in a regression). But I think that is statistically
> speaking that is not very satisfactory, in particular if the
> application does not give any indication what weight to use.

Yes, this is a grey area, where different disciplines approach things 
differently. Looking at the data many times is of course a problem. Not 
infrequently, the "accepted" type of weights for a discipline is the one 
chosen, but this isn't a satisfactory answer. Opinions?


> Any hints?
> Best,
> Stefan
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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.Bivand at nhh.no

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