Hi Marie, I think you can try linear combination fitting, but you'll have to build in the uncertainty in normalization in to your own estimates of uncertainty.
If you don't check the box that says "force weights to sum to 1," then you can allow for normalization errors in your sample. If your standards also have only short energy ranges, then there's nothing you can do about that, though. As I said, you'll just have to build them in to your uncertainty. If you are unsure of the edge jump of a standard to 20%, then the contribution of that standard to the linear combination fit is uncertain by 20%. Uncertainty in normalization is one of the leading contributions to the uncertainty that should be associated with linear combination fitting, even when the energy ranges are sufficient. In a case like yours, they're bigger than they could have been, but it doesn't mean you can't use linear combination analysis at all. --Scott Calvin Sarah Lawrence College On Aug 8, 2012, at 1:17 PM, Marie Zwetsloot wrote: > Hi Scott Calvin, > > Thanks for your help. Yes, this is as far as my pre- and post-edge range go. > I realized I should have made them longer; it was my first time doing this > and wasnt aware that i should lengthen my pre and post-edge for later on > analysis. This will be good lesson for the future. > > So you would not recommend doing linear combination fitting? I was planning > on trying it out.. But I wouldnt want to do it if with my pre- and post-edge > range, I am bound to derive wrong conclusions from the data. > > Best, > Marie > _______________________________________________ > Ifeffit mailing list > Ifeffit@millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit _______________________________________________ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
