Thank you Scott, I guess that is a refinement of my question concerning R-factor.' Chris ******************************** Christopher J. Patridge, PhD NRC Post Doctoral Research Associate Naval Research Laboratory Washington, DC 20375 Cell: 315-529-0501 On 1/15/2013 9:39 AM, Scott Calvin wrote:
Hi Chris,
I don't see a reason to think that data is a glitch. For one thing, it's not consistent across datasets. The features also look smooth, and not so glitch-like. The spike around 8.2 inverse angstroms in some of the datasets looks a bit more like a glitch, but it's fairly modest and narrow enough not to mess you up too much.
The spacing of those features look OK--there's a double feature in some of the datasets around 6-7 inverse angstroms; it's plausible there would be another reature like that above it. In fact, I can make an argument that there's some kind of beating going on that gives a shoulder at 3.5-5, a double peak at 5-7, and two peaks at 7-8 inverse angstroms.
So I would recommend including that data and seeing what it does to your fits. If that range is garbage, your fits will probably reject it.
As for your second question, R-factors are always a kind of average across the data, by definition. So "total" mismatch doesn't really make sense. Off-hand, though, I don't recall how ifeffit weights the data for the purposes of calculating R-factors for multiple datasets, and that may be your question.
--Scott Calvin Sarah Lawrence College
On Jan 15, 2013, at 9:21 AM, Christopher Patridge wrote:
Hello Users,
I was looking for an opinion about the chi(k) signal in a set of data I am analyzing. Brief background, this is a set of in-situ XAS data collected at the Fe K edge from a working electrochemical cell at a range of potentials during charge; I did not collect the data. I suspect the feature at ~ 8 angstroms-1, although present in all the spectra is noise or glitch and wondered if I am being overly cautious?
My conservative range ( k = 2-7 and R = 1-2) really constrains the model Nidp = 3.31. Luckily, multiple datasets ( 8 ) to the rescue to give me some flexibility. In a multiple dataset fitting, is the R-factor of the whole set just the average or total mismatch across all the datasets or it calculated another way?
Working towards happiness,
Chris Patridge
-- ******************************** Christopher J. Patridge, PhD NRC Post Doctoral Research Associate Naval Research Laboratory Washington, DC 20375 Cell: 315-529-0501
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