[R-sig-Geo] Spatial Regression

[Roger Bivand]

On Fri, 19 Jun 2009, youngbin wrote:

> Hi,
>
> 1. While conducting spatial regression models, R does not directly provide
> the Rsquared values. Does anybody have an idea how to get the Pseudo
> Rsquared values in spatial regression models?

The models are fitted with maximum likelihood, so R squared is not a very 
suitable measure, although I'm sure you can find various ways of computing 
them. On the other hand, you can also get the AIC and log-likelihood for 
OLS and some other models, and they also provide a way of comparing 
models.

>
> 2. Regarding spatial regression models, how to conduct the general spatial
> model which both the lag and error are included?
>

This is not provided, and is not even well understood in spatial 
statistics (there are very complicated interactions between the lag and 
error components). Spatial Durbin models do provide a general structure 
within which both lag and error models nest. If both spatial coefficients 
are significant in a general model, you know with little chance of mistake 
that your model is badly misspecified, I'm afraid. The only possible 
alternative is that you have well-motivated behavioural models for both 
processes and their interactions.

Hope this helps,

Roger

> Thanks
>
> youngbin
>
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-- 
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.Bivand at nhh.no