Hi Shaofeng,

Thanks for providing a thorough description of what you did in the Word file—it 
makes it much easier to comment!

I wouldn’t say that sigma2 is not important, in this case. I would say, 
instead, that your fits have not yet successfully distinguished between the 
different proposed models, although some of those models yields significantly 
different values for sigma2.

Here’s my summary of what I’m seeing in your file and from your description:

The Hamilton test doesn’t indicate the differences between fits are 
statistically significant.

The Ba3(AsO4)2 model yields E0’s a bit smaller than the corresponding standard 
(although with overlapping error bars) and sigma2’s significantly larger. The 
larger sigma2 could just indicate it’s somewhat more disordered. I certainly 
can’t reject this model on the basis of the information you’ve provided, but it 
seems a little less likely than the others.

The BaHAsO4*H2O model yields parameters almost identical to the corresponding 
standard. Yay! The results are therefore consistent with the sample being 
BaHAsO4*H2O.

The C2 model again yields parameters that are a bit different from the fits to 
the standards. The sigma2’s are, as you mentioned, small. The E0’s are also 
large compared to the standard, although the error bars overlap.

This raises, for me, a question: did you run a fit with the BaHAsO4*H2O 
standard using the C2 model? I know that’s not the structure you expect for the 
standard, but it would be very nice to know if using that model with the 
standard also yields small sigma2’s, big E0’s, and smaller R-factors. If that 
happens, then you’d gain confidence that you had BaHAsO4*H2O, but you also 
wouldn’t have any evidence that the C2 model was a better description of your 
samples than just the regular BaHAsO4*H2O structure. If, on the other hand, the 
C2 model doesn’t yield a similar set of results for the standard as it did for 
the sample, then you’ve got some more investigating to do.

Does that make sense?




On Jan 8, 2017, at 6:53 AM, Shaofeng Wang 
<wangshaof...@iae.ac.cn<mailto:wangshaof...@iae.ac.cn>> wrote:

Dear Scott and demter users,

I also tried to use BaHAsO4 crystallographic data as the initial model for 
fitting of the EXAFS data. Please see the attached file. It was found the 
sigma2 was around 0.0012-0.0014. The Hamilton tests also show the improvement 
was not significant (> >0.05). But thease results could be considered to be 
better than using DFT optimized Configuration C2 as the initial model. This 
reuslt may imply the sigma2 is strongly denpendent on the initial model. Does 
this mean the sigma2 is not so important to determine the fitting quality?

Regards,

Shaofeng

--------------------------------------
Shaofeng Wang, Ph.D of Geochemistry
Environmental Molecular Science Group
Institute of Applied Ecology, Chinese Academy of Sciences
Shenyang, 110016, China
wangshaof...@iae.ac.cn<mailto:wangshaof...@iae.ac.cn>
www.iae.cas.cn


From: Scott Calvin<mailto:scal...@sarahlawrence.edu>
Sent: Friday, January 06, 2017 3:34 AM
To: XAFS Analysis using Ifeffit<mailto:ifeffit@millenia.cars.aps.anl.gov>
Cc: Shaofeng Wang<mailto:wangshaof...@iae.ac.cn>
Subject: Re: about sigma2 for exafs fitting

Hi Shaofeng,

The parameter b does not have to do solely with the difference in N_var between 
the two fits! As I say in the book,

“Changes in the theoretical standards used by the model can often be accounted 
for as if they were changes in parameters. For example, if fit A assumed that 
the nearest neighbors were oxygen and included coordination number, bond 
length, and MSRD for those oxygen atoms as free parameters, while fit B assumed 
the nearest neighbors were sulfur and used the same three parameters, then a 
Hamilton test could be applied with the assumption that those three parameters 
were “changed”—instead of applying to oxygen, they now apply to sulfur. If E0 
and S02 were also free parameters, they would not be considered to be changed, 
as they are primarily a property of the absorber, not the scatterer.”

In your case, it looks to me like two or three parameters are changed between 
models (I count four free parameters in your table, one of which is E0, so I’m 
not sure why you say there are only three…is there another constraint?) Suppose 
there are two free parameters changed. b = 2/2 = 1.

x is the ratio of R-factors between the fits.

Using the values you list below, then, gives a result of 0.64, which indicates 
such variation is quite likely to have taken place by chance.

You chose the worst case of your three, though; the pH 3 case. The pH 10 case 
shows the most improvement in the R-factor with x = 0.007/0.012 = 0.58. The 
probability of getting that much improvement by chance drops to 0.30—less 
likely, but still pretty close to a coin flip.

Even the fact that you got all three to show improvement doesn’t quite reach 
the 95% confidence level, although it’s becoming suggestive.

Why, then, are fits that seem to have much lower R-factors not attaining 
statistical significance? The main culprit is that you have a relatively small 
number of independent points for studying this kind of system.

So where’s that leave you?

I’ll stand by the results of the Hamilton test…there’s not quite enough data 
here, on its own, for me to decide in favor of your second model. If you have 
other evidence pointing in that direction, these results could be used as 
supporting evidence. But with the combination of the closeness of fit not 
improving to a statistically significant degree and the sigma2 taking on an 
unusual (but not impossible) value, there needs to be more to the argument, in 
my opinion.

Best,
Scott Calvin
Lehman College of the City University of New York

On Jan 5, 2017, at 12:19 AM, Shaofeng Wang 
<wangshaof...@iae.ac.cn<mailto:wangshaof...@iae.ac.cn>> wrote:

Dear Scott,

I have learned the Hamilton test. However, this method seems not suitable to 
distinguish our results because the Nvar are same for the two fittings (3 when 
S02 was fixed). So the b value should be zero and the calculator on the website 
 http://www.danielsoper.com/statcalc/calculator.aspx?id=37 can not carry on.

In addition, I am not sure the value x. Is it the ratio of R-factors between 
two fits? I calculated the results using a=2.18 (Nidp and variables (Nvar) were 
7.35 and 3), b=0.00001, and x=0.818 (the ratio of two R-factors) and got the 
Regularized lower incomplete beta function of 0.00000807. Does it mean 
something?

Cheers,

Shaofeng

--------------------------------------
Shaofeng Wang, Ph.D of Geochemistry
Environmental Molecular Science Group
Institute of Applied Ecology, Chinese Academy of Sciences
Shenyang, 110016, China
wangshaof...@iae.ac.cn<mailto:wangshaof...@iae.ac.cn>
www.iae.cas.cn<http://www.iae.cas.cn>


From: Scott Calvin<mailto:scal...@sarahlawrence.edu>
Sent: Thursday, January 05, 2017 11:50 AM
To: XAFS Analysis using Ifeffit<mailto:ifeffit@millenia.cars.aps.anl.gov>
Cc: Shaofeng Wang<mailto:wangshaof...@iae.ac.cn>
Subject: Fwd: about sigma2 for exafs fitting

Shaofeng has given me permission to repost her question here on the ifeffit 
mailing list. It is quoted below my response.

Dear Shaofeng,

As Bruce and I said before, a sigma2 of 0.0007 A^2 is not impossible, although 
it indicates less disorder than is typically present. Your attached table does 
seem to show some improvement by using the model from the hydrogen-containing 
structure as compared to the arsenate. A more rigorous test for statistical 
improvement can be conducted using the Hamilton test (you mentioned you’ve 
consulted XAFS for Everyone; full details of the Hamilton test are given there).

It’s also encouraging that the uncertainties on your sigma2 determinations 
using the hydrogen-containing model are quite small; it appears that the fit is 
not getting confused by correlations even though it’s fitting both coordination 
number and sigma2, as that would generally also cause high uncertainties in the 
correlated parameters.

Is such a stiff sigma2 reasonable in this case? I have no idea. I just don’t 
know enough about this particular system; perhaps someone else on the list 
does. Oh, and one other question—was the data collected at room temperature? If 
it were collected at cryogenic temperatures, that would tend to reduce thermal 
disorder and thus lower sigma2’s.

Even if no one on the list has insight in to this particular system, anyone 
have good published examples of room-temperature systems with sigma2’s < 0.001? 
It might help Shaofeng with her referee…

Best,

Scott Calvin
Lehman College of the City University of New York

P. S. I certainly hope no reviewer is using the “typical values” I provide for 
parameters in XAFS for Everyone as rigid criteria for rejecting results! It is 
most certainly not the way I use them in the book. Some systems actually are 
atypical!

Begin forwarded message:

From: Shaofeng Wang <wangshaof...@iae.ac.cn<mailto:wangshaof...@iae.ac.cn>>
Subject: about sigma2 for exafs fitting
Date: January 4, 2017 at 8:31:33 PM CST
To: <scal...@sarahlawrence.edu<mailto:scal...@sarahlawrence.edu>>
Reply-To: Shaofeng Wang <wangshaof...@iae.ac.cn<mailto:wangshaof...@iae.ac.cn>>

Dear Dr. Calvin,

I am a research from China. I know you are an expert on XAFS analysis. So I 
write this letter to you for some xafs analysisi problem.

Recently, I am attempting to study the incorporation of arsenate into the 
barite structure. To investigate the species of arsenate in barite, I fitted 
the exafs data using Ba3(AsO4)2 and a dft optimized structure with HAsO4 
incorporated in barite supercell (configuration C2), respectively and got some 
results. Please see the attached table. Smaller reduced chi2 and R-factor were 
obtained by using configuration C2 as the initial model. Does this mean the 
species of arsenate in barite is more likely to be HAsO42- instead of AsO43- ? 
We also have other evidences including XANES and vibrational spectroscopy to 
support this conclusion. However, using C2 as the initial model we obtained 
samll sigma2 (~0.0007). This seems too small and out of the normal range (0.002 
每 0.03) as you mentioned in your publications (XAFS for everyone). So, my 
question is if our data are reasonable. If yes, could you provid some 
references to support?

By the way, I asked simialr question on the ifeffit forum and you gave me some 
answer. However, the reviewer was not convinced and he insited on that sigma2 
must be in the range of 0.002-0.03. How can I response this question?

Any help is very appreciated.

Best regards,

Shaofeng



--------------------------------------
Shaofeng Wang, Ph.D of Geochemistry
Environmental Molecular Science Group
Institute of Applied Ecology, Chinese Academy of Sciences
Shenyang, 110016, China
wangshaof...@iae.ac.cn<mailto:wangshaof...@iae.ac.cn>
www.iae.cas.cn<http://www.iae.cas.cn/>


<EXAFS fitting parameters.docx>

_______________________________________________
Ifeffit mailing list
Ifeffit@millenia.cars.aps.anl.gov
http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit
Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit

Reply via email to