On Mon, 17 Aug 2009, Michael Haenlein wrote:
Dear Roger,
Thanks very much for your reply!
I think what the reviewer is referring to is a lagsarlm() model -- thanks
very much for bringing this functionality to my attention!
I just tried to fit such a model but I get an error message: "Error: Cannot
allocate vector of size 340.5 MB".
I assume this is because my network is very large:
Number of regions: 6681
Number of nonzero links: 39770
Percentage nonzero weights: 0.08909896
Average number of links: 5.952702
Non-symmetric neighbours list
?larsarlm and see method="Matrix". lagsarlm() is not the same model as
errorsarlm(). It will also run slowly in the sparse matrix version; I
suggest using errorsarlm() which does include the spatial autocorrelation
of the error in the model, rather than the spatial autocorrelation of the
dependent variable, so is better aligned with what lm.morantest() was
testing. Both will give likelihood ratio tests of the significance of the
spatial coefficient, but lagsarlm() only gives LR tests of the
coefficients on the x, while with errorsarlm(), you get more-or-less
regular t-tests (they are z-tests because the coefficient standard errors
are the asymptotic ones).
Unless you have a substantive hypothesis for how y_i affects y_j
irrespective of the x variables, errorsalm() may be a safer fallback,
because it is only saying that there is some residual autocorrelation in
the aspatial model, and that is what gets modelled.
Best wishes,
Roger
I'm working on Lenovo Thinkpad (X300) with Windows Vista Business, SP 2 and
2.00 GB RAM.
Would you know whether there is any chance to run this model without
upgrading my RAM?
My current memory.limit() in R is 1535 which seems as far as I can get with
2.00 GB RAM.
Otherwise I might need to find someone with a more powerful machine than
mine.
Thanks very much again for having pointed me towards lagsarlm()!
Best,
Michael
-----Original Message-----
From: Roger Bivand [mailto:roger.biv...@nhh.no]
Sent: Montag, 17. August 2009 14:30
To: Haenlein, Michael
Cc: r-sig-geo@stat.math.ethz.ch
Subject: Re: [R-sig-Geo] Question spdep package - Moran's I
On Mon, 17 Aug 2009, Haenlein, Michael wrote:
If the referee is refering to the social networks literature, you will have
to find out what "one step" means there, if anything.
It is not a term used in connection with Moran's I for spatial data.
If you believe that the referee's "one step" might be met by fitting a model
including both the x variables and the dependence in either y or the
residuals of the regression, look at lagsarlm() and errorsarlm(). Maybe
check against the Ward/Gleditsch "Spatial regression models" Sage volume if
need be.
When working across disciplines, nothing constitutes absolute authority in
this way. Testing residuals ought to be OK, but see Schabenberger & Gotway
for caveats (especially about concluding that autocorrelation is present
when the real problem is model misspecification).
Hope this helps,
Roger
--
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.biv...@nhh.no
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