conditional autoregressive models
The main catch would be to make sure that W is symmetric, since the variance becomes (I - rW)-1 not the cross product as in SAR (which is guaranteed to be symmetric, irrespective of W). Also, the EGLS part would be slightly different, since what is needed is X'(I - rW)X not X'(I - rW)'(I - rW)X. More fundamentally though, one should make sure there is a good reason to use CAR rather than SAR, they imply different correlation structures but also different conceptual models. L.
On Thursday, October 30, 2003, at 07:03 AM, Roger Bivand wrote:
On Thu, 30 Oct 2003, giovanna jona lasinio wrote:
Does anyone know how to estimate via ML a conditional autoregressive model (CAR as in Cressie 1993) using R?
Not yet. As Brian Ripley pointed out in R News in 2001, where functionality has been available in S-PLUS SpatialStats, there has been less incentive to write R code. My guess would be that if one used errorsarlm() in spdep as a template (with the functions being optimised) then it wouldn't be too difficult to do - but returning an object of a "carlm" class, for example. Next print(), anova(), and summary() classes. Would anyone like to help? Roger
Thanks Giovanna Jona Lasinio DSPSA University of Rome "La Sapienza"
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-- 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
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