Matt,
> When it comes down to compare fits
using different models, which is
> the relevant parameter? Chi square (and reduced) or R-factor? I
have
> fits with smaller chi square and larger Rfactor and
viceversa...
This is definitely a FAQ, so I put the answer at
http://cars9.uchicago.edu/cgi-bin/ifeffit/faqwiz?req=show&file=faq08.013.htp
thanks.
> Is it possible that a rationale
would be that when the models to
> compare have the same number of atoms these parameters go in
> parallel? And that when the number of atoms is different one
must
> rely more on chi square rather than R-factor (or viceversa)?
I'm not sure I understnad this: I'd say the number of atoms
or
paths, or anything else that describes the complexity of the
model, is NOT important. What's important is how well the
specified variables cause the model to
match the data.
I think here below is the answer I was looking for (taken from
the link above):
Either of these
parameters can be used to compare different fits if the number of
varibles and data k- and R-ranges are the same for the two
models.
Thanks!
Stefano
--
____________________________________________
Stefano Ciurli
Professor of Chemistry
Department of Agro-Environmental Science and Technology
University of Bologna
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Italy
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