Dear list members,
I posted a question about log-likelihood in slm models earlier. The
background was that I wanted to compare spatial (slm) and non-spatial (lm)
models via AIC. However, the lm and slm models seem to be structurally (or
in their optimization technique) too different, so that their
log-likelihoods are incomparable. Therefore, I thought that, instead of
using the log-likelihood of the lm models, I could use the log-likelihood
from an slm model with the spatial parameter rho set to 0. I accomplished
this indirectly through a likelihood ratio test (lrt.slm), which allows me
to control the parameter settings for the reduced model. However, I would
prefer to be able to do this directly so that I can see whether the
resulting model is really similar in coefficients and all to an lm model.
So my questions are
a) how do I set the parameter rho (called "param1" in the slm) to 0 when
running the model?
b) is the above line of thinking correct?
Thank you
Volker Bahn
_______________________________
volker.bahn@gmx.net
volker.bahn@umit.maine.edu
Dept. of Wildlife Ecology - Rm. 210
University of Maine
5755 Nutting Hall
Orono, Maine
04469-5755, USA
Tel: (207) 581 2799
Fax: (207) 581 2858
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