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st: RE: Testing for Spatial Autocorrelation in Residuals


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Testing for Spatial Autocorrelation in Residuals
Date   Mon, 10 Mar 2008 12:50:14 -0000

Allan refers to -spautoc- (SSC) and -gwr- (STB), both user-written programs. 

In addition, a more substantial suite is Maurizio Pisati's stuff, also in 
the STB. -search pisati, author-. 

I was the author of -spautoc-. I never got round to implementing a regression
residuals flavour of that, nor is it on my agenda. But you should find that starting from -spautoc- 
and adding code would be easier than starting from scratch. 

That said, my general impression is that you are on your own for the most of the things 
you ask for, i.e. you would need to write the code yourself. However, the import of 
your letter is that you want formal tests for autocorrelation. Often it's as or more useful
to map residuals or to do a Moran scatter plot, i.e. the spatial equivalent of a scatter plot
of residual vs L. residual. (-spautoc- calculates weighted means of neighbouring values given 
information on neighbours.) 

Nick
n.j.cox@durham.ac.uk 

Allan Joseph Medwick

I would like to examine the residuals from a Poisson and a Negative
Binomial model for spatial autocorrelation.  I know that -spautoc-
will calculate Moran and Geary measures of autocorrelation, but I have
read that the "regular" Moran's I calculation is not appropriate for
residuals.  Is there a way to check the deviance and Pearson residuals
from a Poisson or Negative Binomial model in Stata for
autocorrelation?  Can Anscombe residuals be used in the analysis?  Are
there any additional tests besides the Moran and Geary measures that
would be appropriate to check?  Any other suggestions?

If there is spatial autocorrelation in the error term, is there a way
to model this in Stata?  Would -gwr- be the best choice?


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