Hello folks, I am sure this is an easy question answered many times, but I need some refresh: 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... 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)? Oh well. Stefano -- ____________________________________________ Stefano Ciurli Professor of Chemistry Department of Agro-Environmental Science and Technology University of Bologna Viale Giuseppe Fanin, 40 I-40127 Bologna Italy Phone: +39-051-209-6204 Fax: +39-051-209-6203 "Fatti non foste a viver come bruti, ma per seguir virtute e canoscenza" Dante Alighieri - Inferno - Canto XXVI "Ihr seid bestimmt, nicht Tieren gleich zu leben, Nein, Tugend zu erringen und Erkenntnis" "Ye were not form'd to live the life of brutes, But virtue to pursue and knowledge high"
Stefano,
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
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. --Matt
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 Viale Giuseppe Fanin, 40 I-40127 Bologna Italy Phone: +39-051-209-6204 Fax: +39-051-209-6203 "Fatti non foste a viver come bruti, ma per seguir virtute e canoscenza" Dante Alighieri - Inferno - Canto XXVI "Ihr seid bestimmt, nicht Tieren gleich zu leben, Nein, Tugend zu erringen und Erkenntnis" "Ye were not form'd to live the life of brutes, But virtue to pursue and knowledge high"
participants (2)
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Matt Newville -
Stefano Ciurli