I suggest that you use CrimeStat. It reads dat files. It will calculate a
Moran's I and Geary's C and test significance. It also has several clustering
routines with monte carlo simulation. It is available FREE at
http://www.icpsr.umich.edu/NACJD/crimestat.html
Richard Block
Department of Sociology
Loyola University
6525 N Sheridan Rd.
Chicago IL 60626
Telephone 773 508 3454
FAX 773 508 7099
email [EMAIL PROTECTED]
>>> "[EMAIL PROTECTED]" <[EMAIL PROTECTED]> 02/25/05 6:07 AM >>>
Dear all,
I have been trying to test the statistical significance
of spatial clustering of a continuous variable X.
As an analogy to Moran's I,
I calculated the following statistics:
A1 = Sigma of Distance(i,j) * (Xi - Xj)**2 for all the
combinations of locations, i and j.
A2 = Sigma of ( 1/Distance(i,j) ) * (Xi - Xj)**2 for all the
combinations of locations, i and j.
I thought A1 would be unusually large and A2 would be unusually
small if X is spatially clustered.
Locations of all observations were randomly permutated many times
(e.g. 100000), thereby a unimodal distribution was obtained for
each of A1 and A2. Then, P value was calculated for
actual A1 and A2.
As a result, P value for A1 and P value for A2 were very different.
The above assumption of mine is correct?
Your suggestion of any sort would be appreciated.
Yoshiro Nagao
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