Thanks to all for taking the time to discuss my concerns. To clarify, both fits were done with exactly the same parameters. So, I believe Bruce's description (below) best explains what is happening. I also realize that my R-factors are rather large compared to the norm for very well-ordered systems. I am, however, fitting protein data that are characteristically not well-ordered. Thanks again for your time, concerns, and suggestions. They were all much appreciated. alison Alison Costello University of New Mexico MSC03 2060 1 University of New Mexico Albuquerque, NM 87131
Viktor and Anatoly are most certainly correct that you parameters should be consistent between the k and q fits. That is probably the bottom line in this discussion.
But as long as we are talking about R-factors....
In the example you give here, it seems to me that you are seeing the interplay of two different aspects of the calculation. In the k-space R factor, the R-factor includes high frequency Fourier components -- both structural and noise. (That is, the R factor considers differences between data and theory and the data includes high frequency pieces in the k-space fit.) The q-space fit has had the high frequency stuff removed, but has the factor of two given that it's a complex function. Those two competing parts of the calculation should explain away the values you quote.
B
-- Bruce Ravel ----------------------------------- bravel@anl.gov -or- ravel@phys.washington.edu Environmental Research Division, Building 203, Room E-165 Argonne National Laboratory phone: (1) 630 252 5033 Argonne IL 60439, USA fax: (1) 630 252 9793
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