R help - Sep 2002 - Question about spatial statistics

I?m tryng  to use the SPDEP package in my research in the field of
population genetics. My data set
has the following format:

 -  x and y : coordinates,
-  Z: allelic frequency in  each loci (in a total of 8 locis) - this
variable can assume the values  0 ; 0.5 or 1.

 The objective is to verify if there is a possible spatial
autocorrelation structure of the allelic frequency in a population of
natives trees (copaifera langsdorffii).
I had some doubts about the package:

1)  Is the package suitable to analyze this kind of data?
2)  Are the spatial autocorrelation tests in the package suitable for
this analysis?
3)  If it is, what are the steps needed to carry out the Moran's I or
others tests ?

Any help will be welcome.
Regards and
Thank you very much.

Jo?o Marcos Louzada
Federal University of Lavras - Brasil

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On Tue, 10 Sep 2002, washington santos da silva wrote:
> I?m tryng  to use the SPDEP package in my research in the field of
> population genetics. My data set
> has the following format:
> 
>  -  x and y : coordinates,
> -  Z: allelic frequency in  each loci (in a total of 8 locis) - this
> variable can assume the values  0 ; 0.5 or 1.
> 
>  The objective is to verify if there is a possible spatial
> autocorrelation structure of the allelic frequency in a population of
> natives trees (copaifera langsdorffii).
> I had some doubts about the package:
> 
> 1)  Is the package suitable to analyze this kind of data?
> 2)  Are the spatial autocorrelation tests in the package suitable for
> this analysis?
> 3)  If it is, what are the steps needed to carry out the Moran's I or
> others tests ?
> 
The package may or may not be what you need, depending on how you - as the 
person knowing the field data and the science - conceptualise the spatial 
process. I have code from Cliff & Ord 1981 for Moran's I for ordinal
data
(ordered factor) that I will include in the next release of the package, 
but - as in many spatial data analysis situations - you usually need to 
try several alternative approaches, of which mapping the data is often the 
key one.
> Any help will be welcome.
> Regards and
> Thank you very much.
> 
> Jo?o Marcos Louzada
> Federal University of Lavras - Brasil
> 
> 
-- 
Roger Bivand
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
and: Department of Geography and Regional Development, University of
Gdansk, al. Mar. J. Pilsudskiego 46, PL-81 378 Gdynia, Poland.

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