Hi Dan, Why are you using only one delr value and two dE values? I would suggest that you try it the other way around. two or more delr values with only one dE value. When you try the different models compare the reduced-chi-square values as you are doing but also look at the Backfourier transfrom of the data and the fit - or the chi(k) data if it is clean. Are they crossing zero at the same places. Do they miss more at low q or high q? Missing at low q/k would suggest separate dE values while missing at high q/k would suggest separate delr values. Would your model be better described by using an overall expansion/contraction term rather than one delr value? Using one delr means that all the paths move by -0.01 angstroms. Using one expansion term would allow all paths to contract by 0.1% which might be more reasonable. So that the long paths shrink in more than the short paths. To use a expansion term use the special "reff" variable which stands for the "effective r" i.e. the effective half path length. set delr1 = alpha*reff set delr2 = alpha*reff guess alpha= -0.01 -yes please drop the third cummulant. HTH Shelly
-----Original Message----- From: dmc@pdx.edu [mailto:dmc@pdx.edu] Sent: Tuesday, August 17, 2004 1:24 PM To: XAFS Analysis using Ifeffit Subject: [Ifeffit] MoS2 fit
Hi Mailing list,
Well, the chief concern I have with my fit now is that I have some negative parameters (delr and e0_1):
Guess parameters +/- uncertainties (initial guess):
amp = 0.7709790 +/- 0.0631820 e0 = 1.1165150 +/- 1.0100360 delr = -0.0106440 +/- 0.0077110 ss = 0.0032510 +/- 0.0005200 e0_1 = -4.6848070 +/- 1.7781210 third = 0.0000370 +/- 0.0001070
So, I guess I can drop the third cumulant.
This is a fit using 6 paths (1,2,3,6 are single scatterers) These are the results this time around:
Reduced Chi-square = 410.285252396 R-factor = 0.014599348
As you can see I am still using two e0's, it is still dramatically improving the fit. Without: Reduced Chi-square = 1133.485950636 R-factor = 0.044551155
any advice welcomed, Dan
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