Hi,
   This is very interesting. I would like to know a little bit more about
how to use glist=argument to reduce weights on observations selected as
members of an edge set and how to identify such members.
  Thanks in advance.
Laurence

2012/8/25 Roger Bivand <Roger.Bivand@nhh.no>

> On Thu, 23 Aug 2012, Kitty Lee wrote:
>
>  Hi. I have some study areas that are very irregularly shaped. I wonder if
>> there is a way to adjust for edge effect in computing Moran's I or Geary C?
>>
>
> The typical approach would be through the weights matrix, depending on how
> W is constructed. If you row-standardise, edge observations will be
> stressed, but with binary weights they are less salient. You could also
> intervene directly to reduce weights on observations selected as members of
> an edge set, through the glist= argument in nb2listw().
>
> Hope this helps,
>
> Roger
>
>
>
>> Any leads would be really appreciated.
>>
>> K.
>>
>> ______________________________**_________________
>> R-sig-Geo mailing list
>> R-sig-Geo@r-project.org
>> https://stat.ethz.ch/mailman/**listinfo/r-sig-geo<https://stat.ethz.ch/mailman/listinfo/r-sig-geo>
>>
>>
> --
> Roger Bivand
> Department of Economics, NHH Norwegian School of Economics,
> Helleveien 30, N-5045 Bergen, Norway.
> voice: +47 55 95 93 55; fax +47 55 95 95 43
> e-mail: Roger.Bivand@nhh.no
>
>
> ______________________________**_________________
> R-sig-Geo mailing list
> R-sig-Geo@r-project.org
> https://stat.ethz.ch/mailman/**listinfo/r-sig-geo<https://stat.ethz.ch/mailman/listinfo/r-sig-geo>
>



-- 

Laurence Delattre

Doctorante INRA
Unité Ecodéveloppement
Domaine St-Paul, site Agroparc
CS 40509
84914 Avignon cedex 9
04 32 72 25 85

	[[alternative HTML version deleted]]

