suspect Ruben would note that, under a normal assumption, OLS and ML
coincide. also, I suspect that Ruben's comments also apply to REML
results--altho in that case you may need to restrict inference to random
components. brian
****************************************************************
Brian Gray
USGS Upper Midwest Environmental Sciences Center
575 Lester Avenue, Onalaska, WI 54650
ph 608-783-7550 ext 19, FAX 608-783-8058
[EMAIL PROTECTED]
*****************************************************************
"Ruben Roa"
<[EMAIL PROTECTED]> To: vanessa stelzenm�ller
<[EMAIL PROTECTED]>
Sent by: cc: [EMAIL PROTECTED]
ai-geostats-list@ Subject: Re: AI-GEOSTATS: Akaike's
information criterion (AIC)
unil.ch
12/18/2002 10:26
AM
Please respond to
"Ruben Roa"
>Dear all,
>
>The AIC is used to select the "best" model from a list
>of theoretical functions. I wonder if its necessary
>the models need to be fitted by the same method ?
Yes. The model must be fitted my maximum likelihood.
>Would it be possible to stress the AIC to select the
>"best" model from models which were fitted for example
>by OLS,WLS, REML etc. This means to use AIC to choose
>the model and the fitting method ?
The algebraic expression for the AIC results from the bias in the maximum
log-likelihood of a model as estimator of the mean expected log-likelihood,
this bias being a function of the number of free parameters in the model.
So it only covers those models fitted by maximum likelihood.
Rub�n
http://webmail.udec.cl
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