On 05/26/2016 10:02 AM, Jesús Eduardo Vega Castillo wrote:
Just for clarifying, this is not what I have been doing. I just was
asked to add new independent variables (individual DW factors for each
path) while I am already at the limit of independent points.

I have been using a number of parameter always lower than the number of
independent points. I have also been managing high correlations by not
varying two strongly correlated parameters at the time. But at the end I
do a final fit setting to guess all the parameters, no matter the
correlations, in order to obtain a "true" reduced Chi2 to report which
includes all parameters. Do you consider this procedure right?

Well, "truth" is a difficult concept and isn't really what EXAFS analysis is all about.

When we do an EXAFS analysis we are testing the extent to which data are consistent with a fitting model. The goal is to find a fitting model that is a defensible description of the data and which yields fitting results and uncertainties that are, themselves, defensible and which tell us something that we want to know about the sample which was measured.

Some parameters are highly correlated and there is nothing you can do about it, regardless of how much you might want to. In a one-shell fit, S02 and coordination number are 100% correlated. It doesn't matter how much your thesis advisor wants you to get the "true" coordination number from the one-shell fit, it won't happen.

So, in the end, you settle upon a fitting model and write a paper. In that paper you report on the fitting results. If the referee asks why you chose to fix a certain parameter, you better have a good reason. That's what I mean by "defensible" -- that you can explain and justify all the choices you made when fitting the data.

The "procedure" is that you define a fitting model, press the big Fit button, and interpret the results. The parameters that you float, the parameters that you fix ... they are defensible when you can defend them. "Because the boss wanted two more sigma^2 parameters" is probably not a defensible argument.

Here are a couple of my papers:


I refer you to these not because they are necessarily relevant to your work or even because they are especially good papers. But, in each, I discuss defensibility of fitting model in a situation where there is not nearly enough information in the measured data to properly describe the actual structure of the sample. Perhaps you'll find it helpful to see how I address this issue.


 Bruce Ravel  ------------------------------------ bra...@bnl.gov

 National Institute of Standards and Technology
 Synchrotron Science Group at NSLS-II
 Building 535A
 Upton NY, 11973

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