Hi Bruce, From April 10 to April 19 of this year, there was a thread discussing the basic strategy Abhijeet is using (first under the subject line "High S02" and then "fitting procedure". As I recall, you were busy with something else at the time, and saw there were enough experts answering so that the question would likely be fully addressed. What Abhijeet is doing, I believe, is fitting the first shell first, setting the relevant values, including S02, to those found from the first shell, and then shifting the R-range to fit a new set of paths. He then continues that iterative procedure, shell by shell. A number of people spoke up for that procedure, although concerns were raised as to whether it was the best approach for the particular system being discussed. What Abhijeet was doing before that discussion was: fit the first shell first, set the relevant values to those found from the first shell, and then extend the R-range to fit a new set of paths, continuing this as an iterative procedure. This meant that the fitting range continued to include paths that he was now constraining to their values from a previous fit. My recollection was that was generally agreed on to be bad practice, and the idea of shifting the R-range through narrow bands was offered as an alternative. Having participated in the discussion the first time around, I personally would not choose this procedure for the kind of system Abhijeet is looking at here: a highly crystalline system with strong contributions from paths at a wide range of distances that is expected to be similar to a known structure. But the point may be to practice this procedure for systems where it is more appropriate, in which case it makes sense to try it first on a known system. --Scott Calvin Sarah Lawrence College On Oct 9, 2009, at 11:47 AM, Bruce Ravel wrote:

Abhijeet,

I took a quick peak at your project and I find it very confusing. In the most recent fit, you are fitting only from 3.5 to 4.4 -- the area under the *third* peak in the data. I don't really know how to comment on this project because you have set a large number of parameters to seemingly arbitrary values. From a numerical perspective, the reason for questions 1 and 2 is because you are attempting to fit only a narrow and of the data and you have set the majority of your parameters. That seems an unlikely strategy to me.

I think the best thing you could do would be to fit *all* of your data rather than an arbitrary and small band of it.