- Ifeffit - millenia.cars.aps.anl.gov

Incomplete source tarballs for larch?
by Johan Nilsson 24 Mar '15

24 Mar '15

Dear all, Today I helped a colleague install larch on OSX Yosemite but we ran into some problems using the source tarball from CARS (larch-0.9.24.tar.gz). It was a bit of a learning curve for me as a linux user but we managed to install the prerequisites (exept for epics) using macports and then ran the larch installer without noticing any warnings or errors. The problem after that was that we could not locate the larch binary. The source tarball does not include a 'bin' directory and some other things that are found in the github source so we went ahead and installed larch from the github source instead. After that we could locate the binery and start the interpreter. Did we make some mistake here or are there things missing in the source tarballs? Best regards, Johan Nilsson

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amplitude parameter S02 larger than 1
by huyanyun＠physics.utoronto.ca 23 Mar '15

23 Mar '15

Hi all, I know this question has been asked for many times. S02 is expected to be around, but smaller than 1, a fact that has been explained, such as in the following previous emails, in our mailing list. http://www.mail-archive.com/ifeffit%40millenia.cars.aps.anl.gov/msg02237.ht… http://millenia.cars.aps.anl.gov/pipermail/ifeffit/2003-February/000230.html However, I am continually get S02 value larger than 1 for a series of similar samples when I fit data in Artemis. I think my fit is very good, because my suspected model(based on other technique) could be verified in XAFS analysis (i.e., defensible in physics), the statistics is good ( R=0.01, reduced chi-square=31.4, fit-range:1.5~6 Angstrom, k-range: 3~14 angstrom-1) and all the parameters such as the bond length, sigma2 are physically reasonable. The only thing makes me uncomfortable is that parameter S02 keeps between 1.45 to 1.55 during the fitting. In my system, the absorber atom occupies two crystallographic sites. So I built a model with paths generated from two FEFF calculations. For paths generated from the 1st and 2nd FEFF calculation, the amplitude parameters are set to be S02*P% and S02*(1-P%) respectively, where P% is the first site occupancy percentage. Both S02 and P are free parameters during the fit, and P is an important conclusion I want to extract from XAFS fitting. However, the fit result gives me S02=1.45 ~ 1.55 and P=0.51 ~ 0.56 all the time (i.e., for each path the 'total amplitude' S02*P% or S02*(1-P%) are about 0.7~0.8, smaller than 1). It looks to me that I got a 'perfect' fit but I am not sure if S02 larger than one is defensible. So I have to ask: 1) Is my current fit with S02 larger than one reasonable? If not, what could be suggested to get around it? 2) What's the meaning of S02? It is interpreted in physics that it is a reduced electron excitation parameter, but is it possible that S02 will be affected by any experimental condition? 3) Can anyone share whether you had the multiple site system that gets S02 larger than one? Looking forward to your help. Best, Yanyun

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Installing demeter from source on Yosemite?
by Anders Glans 23 Mar '15

23 Mar '15

Dear all, Has anybody succeeded with installing demeter from source on a Mac? I have attempted to install demeter from source on OS X 10.10.2, but so far without success. I have followed the installation procedure for Installing source code at http://bruceravel.github.io/demeter/pods/installation.pod.html <http://bruceravel.github.io/demeter/pods/installation.pod.html>, except I installed pgplot from source instead of using the install script provided through ifeffit. I don’t get any errors installing either pgplot or ifeffit. All dependencies for demeter should be met: $ sudo perl ./Build.PL Password: Created MYMETA.yml and MYMETA.json Creating new 'Build' script for 'Demeter' version '0.9.21' If all dependencies are met, build and install Demeter by doing: <snip> The build seems to go fine: $ sudo ./Build Simple test for presence of gnuplot ---> found it! Using gnuplot with the x11 terminal. Building Demeter Building Artemis User's Guide Building Athena User's Guide But the tests fail miserably. Already before the actual testing starts, there is a message that loading of Ifeffit.bundle fails: $ sudo ./Build test t/000_ifeffit.t ......... Can't load '/Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle' for module Ifeffit: dlopen(/Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle, 2): Symbol not found: _ifeffit Referenced from: /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle Expected in: flat namespace in /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle at /System/Library/Perl/5.18/darwin-thread-multi-2level/DynaLoader.pm line 194. at t/000_ifeffit.t line 9. Compilation failed in require at t/000_ifeffit.t line 9. BEGIN failed--compilation aborted at t/000_ifeffit.t line 12. # Looks like your test exited with 255 before it could output anything. t/000_ifeffit.t ......... Dubious, test returned 255 (wstat 65280, 0xff00) Failed 6/6 subtests <snip> However, the bundle exists: $ ls -l /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/ total 152 -r-xr-xr-x 1 root wheel 76208 Mar 18 13:09 Ifeffit.bundle and the symbol in question is part of the bundle (well, at least the string exists): $ grep _ifeffit /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/* Binary file /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle matches Does anybody know what is going on? Am I missing something? A couple of more bits of information: $ which ifeffit /usr/local/bin/ifeffit $ ifeffit Ifeffit 1.2.12 Copyright (c) 2005 Matt Newville, Univ of Chicago command-line shell version 1.1 with GNU Readline Ifeffit> testplot %PGPLOT, Unrecognized device type %PGPLOT, Invalid device specification: /AQT %PGPLOT, PGBBUF: selected graphics device is not open %PGPLOT, PGQCI: selected graphics device is not open %PGPLOT, PGQFS: selected graphics device is not open %PGPLOT, PGSCI: selected graphics device is not open %PGPLOT, PGSFS: selected graphics device is not open %PGPLOT, PGSVP: selected graphics device is not open %PGPLOT, PGBBUF: selected graphics device is not open %PGPLOT, PGEBUF: selected graphics device is not open %PGPLOT, PGSVP: selected graphics device is not open %PGPLOT, PGSCI: selected graphics device is not open %PGPLOT, PGSFS: selected graphics device is not open %PGPLOT, PGEBUF: selected graphics device is not open ** plot error: cannot open device: %PGPLOT, Unrecognized device type %PGPLOT, Invalid device specification: /AQT ** plot error: cannot open device: Ifeffit> exit $ which athena /usr/local/bin/athena $ athena dyld: lazy symbol binding failed: Symbol not found: _iff_exec Referenced from: /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle Expected in: flat namespace dyld: Symbol not found: _iff_exec Referenced from: /Library/Perl/5.18/darwin-thread-multi-2level/auto/Ifeffit/Ifeffit.bundle Expected in: flat namespace Trace/BPT trap: 5 Regards, Anders

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Re: [Ifeffit] Breaking down correlationships between parameters
by Rana, Jatinkumar Kantilal 23 Mar '15

23 Mar '15

Hi Bruce, Thanks for your comments and links of your lectures. I forgot to mention that I use Artemis for fitting my data. Best regards, Jatin -----Original Message----- From: ifeffit-bounces(a)millenia.cars.aps.anl.gov [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of ifeffit-request(a)millenia.cars.aps.anl.gov Sent: 23 March, 2015 15:37 To: ifeffit(a)millenia.cars.aps.anl.gov Subject: Ifeffit Digest, Vol 145, Issue 45 Send Ifeffit mailing list submissions to ifeffit(a)millenia.cars.aps.anl.gov To subscribe or unsubscribe via the World Wide Web, visit http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit or, via email, send a message with subject or body 'help' to ifeffit-request(a)millenia.cars.aps.anl.gov You can reach the person managing the list at ifeffit-owner(a)millenia.cars.aps.anl.gov When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." Today's Topics: 1. Re: Breaking down correlationships between parameters (Bruce Ravel) 2. Re: Breaking down correlationships between parameters (Rana, Jatinkumar Kantilal) ---------------------------------------------------------------------- Message: 1 Date: Mon, 23 Mar 2015 09:27:05 -0400 From: Bruce Ravel <bravel(a)bnl.gov> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> Subject: Re: [Ifeffit] Breaking down correlationships between parameters Message-ID: <551014A9.4090604(a)bnl.gov> Content-Type: text/plain; charset=utf-8; format=flowed On 03/23/2015 08:54 AM, Rana, Jatinkumar Kantilal wrote: > The term N*S02 is fitted for each path of the FEFF calculation. So my > question is, even if we know N with a great certainty for some path, > how can we vary both N and S02 for other paths ? or Did I understand > it wrong ? At no point in your emails did you say that you are using Artemis to do your fitting. The comment I am about to make may not, therefore, be relevant to you. In Ifeffit and Larch -- and therefore in Artemis -- we DO NOT fit N*SO2. Fits in Ifeffit, Larch, and Artemis use a set of user-defined parameters as the variables of the fit. As part of the fitting model, the user relates the variables of the fit to the parameters of the EXAFS equation using math expression. This benefit of the generality of the fitting model allows the user to easily encode prior knowledge into a fit. The cost is that the parameters have to be interpreted in some kind of physical context. To answer you question specifically, Artemis allows you to set or float parameters for N and S02 and to define the amplitude term of the EXAFS equation for each path in any way that you see fit. In that way, you can implement all the suggestions that Matt, Scott, and Chris have made. I discuss this in some detail starting at page 35 of this presentation. https://speakerdeck.com/bruceravel/advanced-topics-in-exafs-analysis Among the lectures at http://www.diamond.ac.uk/Beamlines/Spectroscopy/Techniques/XAS.html, this is the one called "Fit Evaluation and Fitting multiple structures". HTH, B -- Bruce Ravel ------------------------------------ bravel(a)bnl.gov National Institute of Standards and Technology Synchrotron Science Group at NSLS-II Building 535A Upton NY, 11973 Homepage: http://bruceravel.github.io/home/ Software: https://github.com/bruceravel Demeter: http://bruceravel.github.io/demeter/ ------------------------------ Message: 2 Date: Mon, 23 Mar 2015 14:36:31 +0000 From: "Rana, Jatinkumar Kantilal" <jatinkumar.rana(a)helmholtz-berlin.de> To: "ifeffit(a)millenia.cars.aps.anl.gov" <ifeffit(a)millenia.cars.aps.anl.gov> Subject: Re: [Ifeffit] Breaking down correlationships between parameters Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE7F0@didag1> Content-Type: text/plain; charset="utf-8" Hi Scott, Thanks for your explanation. It means the reverse can also be true, i.e., I can guess N1 (nearest-neighbors in the first shell) and S02 by setting N2, N3 and N4 to values known from other analysis. I did a quick check by fitting the data. I conducted two fits: 1) setting S02 and guessing only N1 2) guessing both N1 and S02. To my surprise, both the fits gave very similar results, except that the fit#1 refined value of N1 to a higher side, while fit#2 estimated N1 closer to a physically reasonable value (as expected). I always constrained S02 when refining N for any path, due to 100% correlation between them. However, I am surprised to know that they can be refined independently. Best regards, Jatin -----Original Message----- From: ifeffit-bounces(a)millenia.cars.aps.anl.gov [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of ifeffit-request(a)millenia.cars.aps.anl.gov Sent: 23 March, 2015 14:19 To: ifeffit(a)millenia.cars.aps.anl.gov Subject: Ifeffit Digest, Vol 145, Issue 44 Send Ifeffit mailing list submissions to ifeffit(a)millenia.cars.aps.anl.gov To subscribe or unsubscribe via the World Wide Web, visit http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit or, via email, send a message with subject or body 'help' to ifeffit-request(a)millenia.cars.aps.anl.gov You can reach the person managing the list at ifeffit-owner(a)millenia.cars.aps.anl.gov When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." Today's Topics: 1. Re: Breaking down correlationships between parameters (Scott Calvin) ---------------------------------------------------------------------- Message: 1 Date: Mon, 23 Mar 2015 09:18:21 -0400 From: Scott Calvin <scalvin(a)sarahlawrence.edu> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> Subject: Re: [Ifeffit] Breaking down correlationships between parameters Message-ID: <78C1636C-91CF-4C8C-9D48-3EC361BB7237(a)slc.edu> Content-Type: text/plain; charset="utf-8" Hi Jatin, The key is that S02 should be the same for all paths. For example: Suppose you are very confident path 1 has a coordination number of 6, because of prior knowledge you have about the system. Paths 2, 3, and 4 have unknown coordination numbers, however. N1 (i.e. the degeneracy of path 1) you set to 6. You guess S02, N2, N3, and N4. Of course, the way Artemis and Ifeffit implement that, you're writing N1*S02 for the S02 field of Path 1, N2*S02 for the S02 field of Path 2, etc., and then setting N1 = 6 and guessing S02, N2, N3, and N4. There is now enough information for S02, N2, N3, and N4 to each be fitted without 100% correlation. ?Scott Calvin Sarah Lawrence College > On Mar 23, 2015, at 8:54 AM, Rana, Jatinkumar Kantilal <jatinkumar.rana(a)helmholtz-berlin.de> wrote: > > Hi Chris, > > The term N*S02 is fitted for each path of the FEFF calculation. So my question is, even if we know N with a great certainty for some path, how can we vary both N and S02 for other paths ? or Did I understand it wrong ? > > Best regards, > Jatin > > -----Original Message----- > From: ifeffit-bounces(a)millenia.cars.aps.anl.gov > [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of > ifeffit-request(a)millenia.cars.aps.anl.gov > Sent: 23 March, 2015 12:16 > To: ifeffit(a)millenia.cars.aps.anl.gov > Subject: Ifeffit Digest, Vol 145, Issue 42 > > Send Ifeffit mailing list submissions to > ifeffit(a)millenia.cars.aps.anl.gov > > To subscribe or unsubscribe via the World Wide Web, visit > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > or, via email, send a message with subject or body 'help' to > ifeffit-request(a)millenia.cars.aps.anl.gov > > You can reach the person managing the list at > ifeffit-owner(a)millenia.cars.aps.anl.gov > > When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." > > > Today's Topics: > > 1. Re: Breaking down correlationships between parameters > (Rana, Jatinkumar Kantilal) > 2. Re: Breaking down correlationships between parameters > (Chris Patridge) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Mon, 23 Mar 2015 11:00:19 +0000 > From: "Rana, Jatinkumar Kantilal" > <jatinkumar.rana(a)helmholtz-berlin.de> > To: "ifeffit(a)millenia.cars.aps.anl.gov" > <ifeffit(a)millenia.cars.aps.anl.gov> > Subject: Re: [Ifeffit] Breaking down correlationships between > parameters > Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE777@didag1> > Content-Type: text/plain; charset="utf-8" > > Hi Scott, > > Thank you for your comments. Can you please elaborate a little bit more on this "In cases like that, both N for all paths but one and S02 can be fit without 100% correlation." > > Best regards, > Jatin > > -----Original Message----- > From: ifeffit-bounces(a)millenia.cars.aps.anl.gov > [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of > ifeffit-request(a)millenia.cars.aps.anl.gov > Sent: 23 March, 2015 10:16 > To: ifeffit(a)millenia.cars.aps.anl.gov > Subject: Ifeffit Digest, Vol 145, Issue 41 > > Send Ifeffit mailing list submissions to > ifeffit(a)millenia.cars.aps.anl.gov > > To subscribe or unsubscribe via the World Wide Web, visit > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > or, via email, send a message with subject or body 'help' to > ifeffit-request(a)millenia.cars.aps.anl.gov > > You can reach the person managing the list at > ifeffit-owner(a)millenia.cars.aps.anl.gov > > When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." > > > Today's Topics: > > 1. Re: Breaking down correlationships between parameters > (Scott Calvin) > 2. Re: Breaking down correlationships between parameters > (Matt Newville) > 3. Re: Breaking down correlationships between parameters > (Rana, Jatinkumar Kantilal) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Sun, 22 Mar 2015 13:44:28 -0400 > From: Scott Calvin <scalvin(a)sarahlawrence.edu> > To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> > Subject: Re: [Ifeffit] Breaking down correlationships between > parameters > Message-ID: <E0C66911-7AD2-448C-9F64-F03E262D04D7(a)slc.edu> > Content-Type: text/plain; charset="utf-8" > > One side-comment from me: > > On Mar 22, 2015, at 12:52 PM, Matt Newville <newville(a)cars.uchicago.edu<mailto:newville@cars.uchicago.edu>> wrote: > > N and S02 are always 100% correlated (mathematically, not merely by the finite k range). > > Matt is saying that N and S02 are always 100% correlated for a single path. But in some situations you might know N for one path but not others. For example, you might know that the absorbing atom is octahedrally coordinated to oxygen but not be as certain as to next-nearest neighbors, or that there are copper atoms on the corners of a simple cubic lattice with a mixture of atoms at other positions. In cases like that, both N for all paths but one and S02 can be fit without 100% correlation. > > The degeneracy of multiple-scattering paths can often be constrained in terms of the coordination numbers for direct-scattering paths, which can further reduce (not ?break?) the correlation. > > In terms of the main question, I agree with Matt: I don?t think there?s much point in using the line-crossing technique nowadays; fitting using multiple k-weights simultaneously accomplishes the same thing but is a bit easier to interpret statistically. > > ?Scott Calvin > Sarah Lawrence College > -------------- next part -------------- An HTML attachment was > scrubbed... > URL: > <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/201503 > 22/f4e7b7e4/attachment-0001.htm> > > ------------------------------ > > Message: 2 > Date: Sun, 22 Mar 2015 15:56:20 -0500 > From: Matt Newville <newville(a)cars.uchicago.edu> > To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> > Subject: Re: [Ifeffit] Breaking down correlationships between > parameters > Message-ID: > > <CA+7ESbq_s0X3L9rPDDnwAdhx7h6Ptx5-8guCUFTM2OjwkYEerA(a)mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > > On Sun, Mar 22, 2015 at 12:44 PM, Scott Calvin > <scalvin(a)sarahlawrence.edu> > wrote: > >> One side-comment from me: >> >> On Mar 22, 2015, at 12:52 PM, Matt Newville >> <newville(a)cars.uchicago.edu> >> wrote: >> >> N and S02 are always 100% correlated (mathematically, not merely by >> the finite k range). >> >> >> Matt is saying that N and S02 are always 100% correlated *for a >> single path*. But in some situations you might know N for one path >> but not others. For example, you might know that the absorbing atom >> is octahedrally coordinated to oxygen but not be as certain as to >> next-nearest neighbors, or that there are copper atoms on the corners >> of a simple cubic lattice with a mixture of atoms at other positions. >> In cases like that, both N for all paths but one and S02 can be fit without 100% correlation. >> >> > Yes, I completely agree with Scott -- this is a good point that I > neglected. In addition to looking at multiple shells, one might also > consider using temperature or pressure dependence to separate N*S02 and > sigma2. Those aren't without assumptions, and still don't remove the > inherent correlation, but are useful approaches. > > The degeneracy of multiple-scattering paths can often be constrained > in >> terms of the coordination numbers for direct-scattering paths, which >> can further reduce (not ?break?) the correlation. >> >> In terms of the main question, I agree with Matt: I don?t think >> there?s much point in using the line-crossing technique nowadays; >> fitting using multiple k-weights simultaneously accomplishes the same >> thing but is a bit easier to interpret statistically. >> >> ?Scott Calvin >> Sarah Lawrence College >> >> _______________________________________________ >> Ifeffit mailing list >> Ifeffit(a)millenia.cars.aps.anl.gov >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit >> >> > --Matt > -------------- next part -------------- An HTML attachment was > scrubbed... > URL: > <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/201503 > 22/3dd3f763/attachment-0001.htm> > > ------------------------------ > > Message: 3 > Date: Mon, 23 Mar 2015 09:16:02 +0000 > From: "Rana, Jatinkumar Kantilal" > <jatinkumar.rana(a)helmholtz-berlin.de> > To: "ifeffit(a)millenia.cars.aps.anl.gov" > <ifeffit(a)millenia.cars.aps.anl.gov> > Subject: Re: [Ifeffit] Breaking down correlationships between > parameters > Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE755@didag1> > Content-Type: text/plain; charset="utf-8" > > Hi Matt, > > Thank you very much for your detailed explanation. As you pointed out that this approach ignores the statistical significance of fits and assumes that all fits are "good" fits. Also, the point that this approach yields a value of the parameter which is only slightly less correlated with the other one, but not completely removes the correlation. It makes it really clear to me that how this approach works and what are the pros and cons. > > Well, I myself has never tried this approach of minimizing the correlation between N*S02 and sigma2, but I read a lot about it in the literature. With my limited knowledge about the method, I could not judge this approach, although I had my own doubts. > > I truly appreciate your efforts in providing me a deeper insight into this approach. > > Best regards, > Jatin > > -----Original Message----- > From: ifeffit-bounces(a)millenia.cars.aps.anl.gov > [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of > ifeffit-request(a)millenia.cars.aps.anl.gov > Sent: 22 March, 2015 18:00 > To: ifeffit(a)millenia.cars.aps.anl.gov > Subject: Ifeffit Digest, Vol 145, Issue 40 > > Send Ifeffit mailing list submissions to > ifeffit(a)millenia.cars.aps.anl.gov > > To subscribe or unsubscribe via the World Wide Web, visit > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > or, via email, send a message with subject or body 'help' to > ifeffit-request(a)millenia.cars.aps.anl.gov > > You can reach the person managing the list at > ifeffit-owner(a)millenia.cars.aps.anl.gov > > When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." > > > Today's Topics: > > 1. Re: Breaking down correlationships between parameters > (Matt Newville) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Sun, 22 Mar 2015 11:52:30 -0500 > From: Matt Newville <newville(a)cars.uchicago.edu> > To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> > Subject: Re: [Ifeffit] Breaking down correlationships between > parameters > Message-ID: > > <CA+7ESbqcyQHf9XUh2uhk=Lv09An7E9LXxqDTX-X6kRJHy9PFzw(a)mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > > Hi Jatin, > > > On Sat, Mar 21, 2015 at 10:41 AM, Rana, Jatinkumar Kantilal < jatinkumar.rana(a)helmholtz-berlin.de> wrote: > >> Hi Matt, >> >> Thanks a lot for your prompt reply. The method I am referring to is >> not the multiple k-weight fits by constraining N*S02. My apologies >> for not being clear enough. Let's do it again. I am actually >> referring to an approach where we take an advantage of a different >> k-dependence of various parameters to breakdown correlations between >> them. For example, S02 and sigma2. S02 is k-independent and Sigma2 has k^2 dependence. >> >> > Yes, I am familiar with this approach, and I understand that this is what you are using. What I am saying is that this does not work nearly as well as (sometimes) claimed, and is sort of cheating. It ignores the measures of statistical significance. > > In this case, to breakdown correlation between S02 and sigma2, > > > The correlation between N*S02 and sigma2 is inherent to the finite k-range of the EXAFS signal. It cannot be "broken", though it might be reduced. > > >> one can assume a series of S02 values and perform fits using a single >> k-weight each time (say k-weight 1,2 and 3) and record corresponding >> sigma2 values. > > Let us say for k-weight =1, a series of preset S02 values will result > in a >> series of corresponding sigma2 values refined in fits, which can be >> plotted as a straight line in sigma2 vs. S02 plot. > > > OK, one can fit sigma2 with a series of preset values on N*S02. That's fine. But it does NOT lead to an infinitely thin line of sigma2 vs. > N*S02. Each sigma2 value on that line has a width, corresponding to its > uncertainty. In fact, the line you produce nicely demonstrates and > measures the correlation of N*S02 and sigma2 as the slope of this line. > > >> Similar straight lines can be obtained for fits using k-weight = 2 >> and then 3. > > Now, these three lines may intersect at or near some point, which will >> determine the "true" value of parameters independent of k-weight. > > > The different lines (each with finite thickness) will give a *range of > values* for N*S02 and sigma2, not a single value. > > The biggest problem with this approach is that it ignores the relative goodness-of-fits (let's just assume that is 'chi-square' for the purpose of > this discussion) for the fits along these lines. Some fits are better > than others, and this approach completely ignores that fact, and equally importantly ignores the fact that there is a range of values for chi-square > that are consistent with "good". If you include these values, your > linear plot will become contours of chi-square as a function of N*S02 and > sigma2. And, yes, by using different k-weights and k-ranges and so on you > can get overlapping contour plots which may reduce the correlation a small amount when looked at as an ensemble. And you can find a best set of values for N*S02 and sigma2, but *each* of these will have an uncertainty. > > So, you can use this approach to find a good value for N*S02, but it is not breaking the correlation. You can do this by hand. Or you can just do a > fit with datasets with different k-weights and k-ranges. When you do this > as a fit, you will see that the correlation is still fairly large. > > Also, just to be clear, this is absolutely not a "true" value. It is a measured value. Not at all the same thing. > > One can then constrain S02 to a value obtained from the point of >> intersection of three lines and vary sigma2 in a fit. > > > Well, one can certainly set N*S02 to some value and fit sigma2. As I said earlier, this ignores the correlation of N*S02 and sigma2, but does not remove that correlation. > > >> In this particular case, however, the advantage is, S02 does not >> depend on changes inside sample and we have very good estimate of its >> range (say 0.7 >> - 1.0). >> >> Now suppose instead of S02 (which i now set to a reasonable value), I >> am interested in determining N, but it is highly correlated with >> sigma2. Each time when disorder in the sample increases, the sigma2 >> increases and due to its high correlation, N is also overestimated. >> On the other hand, when the disorder in the sample decreases, the >> sigma2 decreases and I can have a "true" estimation of N in the >> sample. Can I still apply the above mentioned approach to break the correlationship between N and sigma2 and get a "true" >> estimation of N, even if disorder is high in my samples ? or it is >> simply not possible due to the fact that both N and sigma2 varies >> with changes inside the sample. >> >> > N and S02 are always 100% correlated (mathematically, not merely by the finite k range). So, to the extent that the approach works at all, you can use it for "N" or "S02". Really, the approach is comparing N*S02 and sigma2, in one case you asserted a value of "N" and projected all changes to "S02" -- you can equally assert "S02" and project all changes to "N". > > To be clear, this is not going to find the "true" value of anything, because no analysis is ever going to find the "true" value -- it's going to find a measured value. > > Finally, the correlation of N*S02 and sigma2 does not imply a bias in the values for N*S02. N*S02 is NOT overestimated because it is highly correlated with sigma2. > > Hope that helps, > > --Matt > -------------- next part -------------- An HTML attachment was > scrubbed... > URL: > <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/201503 > 22/86f5b809/attachment.html> > > ------------------------------ > > _______________________________________________ > Ifeffit mailing list > Ifeffit(a)millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > > > End of Ifeffit Digest, Vol 145, Issue 40 > **************************************** > > ________________________________ > > Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH > > Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. > > Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, > stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph > Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas > Frederking > > Sitz Berlin, AG Charlottenburg, 89 HRB 5583 > > Postadresse: > Hahn-Meitner-Platz 1 > D-14109 Berlin > > http://www.helmholtz-berlin.de > > > > ------------------------------ > > _______________________________________________ > Ifeffit mailing list > Ifeffit(a)millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > > > End of Ifeffit Digest, Vol 145, Issue 41 > **************************************** > > ________________________________ > > Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH > > Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. > > Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, > stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph > Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas > Frederking > > Sitz Berlin, AG Charlottenburg, 89 HRB 5583 > > Postadresse: > Hahn-Meitner-Platz 1 > D-14109 Berlin > > http://www.helmholtz-berlin.de > > > > ------------------------------ > > Message: 2 > Date: Mon, 23 Mar 2015 07:15:05 -0400 > From: Chris Patridge <patridge(a)buffalo.edu> > To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> > Subject: Re: [Ifeffit] Breaking down correlationships between > parameters > Message-ID: <29942DF9-8043-424E-BDCC-9CA19EB4AC9B(a)buffalo.edu> > Content-Type: text/plain; charset=utf-8 > > I think Scott was pointing out that first neighbors may be known with high certainty and therefore you can set this value thereby removing it and slightly reducing the correlations. > > Chris > > Sent from my iPhone > >> On Mar 23, 2015, at 7:00 AM, Rana, Jatinkumar Kantilal <jatinkumar.rana(a)helmholtz-berlin.de> wrote: >> >> Hi Scott, >> >> Thank you for your comments. Can you please elaborate a little bit more on this "In cases like that, both N for all paths but one and S02 can be fit without 100% correlation." >> >> Best regards, >> Jatin >> >> -----Original Message----- >> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov >> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of >> ifeffit-request(a)millenia.cars.aps.anl.gov >> Sent: 23 March, 2015 10:16 >> To: ifeffit(a)millenia.cars.aps.anl.gov >> Subject: Ifeffit Digest, Vol 145, Issue 41 >> >> Send Ifeffit mailing list submissions to >> ifeffit(a)millenia.cars.aps.anl.gov >> >> To subscribe or unsubscribe via the World Wide Web, visit >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit >> or, via email, send a message with subject or body 'help' to >> ifeffit-request(a)millenia.cars.aps.anl.gov >> >> You can reach the person managing the list at >> ifeffit-owner(a)millenia.cars.aps.anl.gov >> >> When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." >> >> >> Today's Topics: >> >> 1. Re: Breaking down correlationships between parameters >> (Scott Calvin) >> 2. Re: Breaking down correlationships between parameters >> (Matt Newville) >> 3. Re: Breaking down correlationships between parameters >> (Rana, Jatinkumar Kantilal) >> >> >> --------------------------------------------------------------------- >> - >> >> Message: 1 >> Date: Sun, 22 Mar 2015 13:44:28 -0400 >> From: Scott Calvin <scalvin(a)sarahlawrence.edu> >> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> >> Subject: Re: [Ifeffit] Breaking down correlationships between >> parameters >> Message-ID: <E0C66911-7AD2-448C-9F64-F03E262D04D7(a)slc.edu> >> Content-Type: text/plain; charset="utf-8" >> >> One side-comment from me: >> >> On Mar 22, 2015, at 12:52 PM, Matt Newville <newville(a)cars.uchicago.edu<mailto:newville@cars.uchicago.edu>> wrote: >> >> N and S02 are always 100% correlated (mathematically, not merely by the finite k range). >> >> Matt is saying that N and S02 are always 100% correlated for a single path. But in some situations you might know N for one path but not others. For example, you might know that the absorbing atom is octahedrally coordinated to oxygen but not be as certain as to next-nearest neighbors, or that there are copper atoms on the corners of a simple cubic lattice with a mixture of atoms at other positions. In cases like that, both N for all paths but one and S02 can be fit without 100% correlation. >> >> The degeneracy of multiple-scattering paths can often be constrained in terms of the coordination numbers for direct-scattering paths, which can further reduce (not ?break?) the correlation. >> >> In terms of the main question, I agree with Matt: I don?t think there?s much point in using the line-crossing technique nowadays; fitting using multiple k-weights simultaneously accomplishes the same thing but is a bit easier to interpret statistically. >> >> ?Scott Calvin >> Sarah Lawrence College >> -------------- next part -------------- An HTML attachment was >> scrubbed... >> URL: >> <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/20150 >> 3 >> 22/f4e7b7e4/attachment-0001.htm> >> >> ------------------------------ >> >> Message: 2 >> Date: Sun, 22 Mar 2015 15:56:20 -0500 >> From: Matt Newville <newville(a)cars.uchicago.edu> >> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> >> Subject: Re: [Ifeffit] Breaking down correlationships between >> parameters >> Message-ID: >> >> <CA+7ESbq_s0X3L9rPDDnwAdhx7h6Ptx5-8guCUFTM2OjwkYEerA(a)mail.gmail.com> >> Content-Type: text/plain; charset="utf-8" >> >> On Sun, Mar 22, 2015 at 12:44 PM, Scott Calvin >> <scalvin(a)sarahlawrence.edu> >> wrote: >> >>> One side-comment from me: >>> >>> On Mar 22, 2015, at 12:52 PM, Matt Newville >>> <newville(a)cars.uchicago.edu> >>> wrote: >>> >>> N and S02 are always 100% correlated (mathematically, not merely by >>> the finite k range). >>> >>> >>> Matt is saying that N and S02 are always 100% correlated *for a >>> single path*. But in some situations you might know N for one path >>> but not others. For example, you might know that the absorbing atom >>> is octahedrally coordinated to oxygen but not be as certain as to >>> next-nearest neighbors, or that there are copper atoms on the >>> corners of a simple cubic lattice with a mixture of atoms at other positions. >>> In cases like that, both N for all paths but one and S02 can be fit without 100% correlation. >> Yes, I completely agree with Scott -- this is a good point that I >> neglected. In addition to looking at multiple shells, one might also >> consider using temperature or pressure dependence to separate N*S02 and >> sigma2. Those aren't without assumptions, and still don't remove the >> inherent correlation, but are useful approaches. >> >> The degeneracy of multiple-scattering paths can often be constrained >> in >>> terms of the coordination numbers for direct-scattering paths, which >>> can further reduce (not ?break?) the correlation. >>> >>> In terms of the main question, I agree with Matt: I don?t think >>> there?s much point in using the line-crossing technique nowadays; >>> fitting using multiple k-weights simultaneously accomplishes the >>> same thing but is a bit easier to interpret statistically. >>> >>> ?Scott Calvin >>> Sarah Lawrence College >>> >>> _______________________________________________ >>> Ifeffit mailing list >>> Ifeffit(a)millenia.cars.aps.anl.gov >>> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit >> --Matt >> -------------- next part -------------- An HTML attachment was >> scrubbed... >> URL: >> <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/20150 >> 3 >> 22/3dd3f763/attachment-0001.htm> >> >> ------------------------------ >> >> Message: 3 >> Date: Mon, 23 Mar 2015 09:16:02 +0000 >> From: "Rana, Jatinkumar Kantilal" >> <jatinkumar.rana(a)helmholtz-berlin.de> >> To: "ifeffit(a)millenia.cars.aps.anl.gov" >> <ifeffit(a)millenia.cars.aps.anl.gov> >> Subject: Re: [Ifeffit] Breaking down correlationships between >> parameters >> Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE755@didag1> >> Content-Type: text/plain; charset="utf-8" >> >> Hi Matt, >> >> Thank you very much for your detailed explanation. As you pointed out that this approach ignores the statistical significance of fits and assumes that all fits are "good" fits. Also, the point that this approach yields a value of the parameter which is only slightly less correlated with the other one, but not completely removes the correlation. It makes it really clear to me that how this approach works and what are the pros and cons. >> >> Well, I myself has never tried this approach of minimizing the correlation between N*S02 and sigma2, but I read a lot about it in the literature. With my limited knowledge about the method, I could not judge this approach, although I had my own doubts. >> >> I truly appreciate your efforts in providing me a deeper insight into this approach. >> >> Best regards, >> Jatin >> >> -----Original Message----- >> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov >> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of >> ifeffit-request(a)millenia.cars.aps.anl.gov >> Sent: 22 March, 2015 18:00 >> To: ifeffit(a)millenia.cars.aps.anl.gov >> Subject: Ifeffit Digest, Vol 145, Issue 40 >> >> Send Ifeffit mailing list submissions to >> ifeffit(a)millenia.cars.aps.anl.gov >> >> To subscribe or unsubscribe via the World Wide Web, visit >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit >> or, via email, send a message with subject or body 'help' to >> ifeffit-request(a)millenia.cars.aps.anl.gov >> >> You can reach the person managing the list at >> ifeffit-owner(a)millenia.cars.aps.anl.gov >> >> When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." >> >> >> Today's Topics: >> >> 1. Re: Breaking down correlationships between parameters >> (Matt Newville) >> >> >> --------------------------------------------------------------------- >> - >> >> Message: 1 >> Date: Sun, 22 Mar 2015 11:52:30 -0500 >> From: Matt Newville <newville(a)cars.uchicago.edu> >> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> >> Subject: Re: [Ifeffit] Breaking down correlationships between >> parameters >> Message-ID: >> >> <CA+7ESbqcyQHf9XUh2uhk=Lv09An7E9LXxqDTX-X6kRJHy9PFzw(a)mail.gmail.com> >> Content-Type: text/plain; charset="utf-8" >> >> Hi Jatin, >> >> >>> On Sat, Mar 21, 2015 at 10:41 AM, Rana, Jatinkumar Kantilal < jatinkumar.rana(a)helmholtz-berlin.de> wrote: >>> >>> Hi Matt, >>> >>> Thanks a lot for your prompt reply. The method I am referring to is >>> not the multiple k-weight fits by constraining N*S02. My apologies >>> for not being clear enough. Let's do it again. I am actually >>> referring to an approach where we take an advantage of a different >>> k-dependence of various parameters to breakdown correlations between >>> them. For example, S02 and sigma2. S02 is k-independent and Sigma2 has k^2 dependence. >> Yes, I am familiar with this approach, and I understand that this is what you are using. What I am saying is that this does not work nearly as well as (sometimes) claimed, and is sort of cheating. It ignores the measures of statistical significance. >> >> In this case, to breakdown correlation between S02 and sigma2, >> >> >> The correlation between N*S02 and sigma2 is inherent to the finite k-range of the EXAFS signal. It cannot be "broken", though it might be reduced. >> >> >>> one can assume a series of S02 values and perform fits using a >>> single k-weight each time (say k-weight 1,2 and 3) and record >>> corresponding >>> sigma2 values. >> >> Let us say for k-weight =1, a series of preset S02 values will result >> in a >>> series of corresponding sigma2 values refined in fits, which can be >>> plotted as a straight line in sigma2 vs. S02 plot. >> >> >> OK, one can fit sigma2 with a series of preset values on N*S02. That's fine. But it does NOT lead to an infinitely thin line of sigma2 vs. >> N*S02. Each sigma2 value on that line has a width, corresponding to its >> uncertainty. In fact, the line you produce nicely demonstrates and >> measures the correlation of N*S02 and sigma2 as the slope of this line. >> >> >>> Similar straight lines can be obtained for fits using k-weight = 2 >>> and then 3. >> >> Now, these three lines may intersect at or near some point, which >> will >>> determine the "true" value of parameters independent of k-weight. >> >> >> The different lines (each with finite thickness) will give a *range >> of >> values* for N*S02 and sigma2, not a single value. >> >> The biggest problem with this approach is that it ignores the relative goodness-of-fits (let's just assume that is 'chi-square' for the purpose of >> this discussion) for the fits along these lines. Some fits are better >> than others, and this approach completely ignores that fact, and equally importantly ignores the fact that there is a range of values for chi-square >> that are consistent with "good". If you include these values, your >> linear plot will become contours of chi-square as a function of N*S02 and >> sigma2. And, yes, by using different k-weights and k-ranges and so on you >> can get overlapping contour plots which may reduce the correlation a small amount when looked at as an ensemble. And you can find a best set of values for N*S02 and sigma2, but *each* of these will have an uncertainty. >> >> So, you can use this approach to find a good value for N*S02, but it is not breaking the correlation. You can do this by hand. Or you can just do a >> fit with datasets with different k-weights and k-ranges. When you do this >> as a fit, you will see that the correlation is still fairly large. >> >> Also, just to be clear, this is absolutely not a "true" value. It is a measured value. Not at all the same thing. >> >> One can then constrain S02 to a value obtained from the point of >>> intersection of three lines and vary sigma2 in a fit. >> >> >> Well, one can certainly set N*S02 to some value and fit sigma2. As I said earlier, this ignores the correlation of N*S02 and sigma2, but does not remove that correlation. >> >> >>> In this particular case, however, the advantage is, S02 does not >>> depend on changes inside sample and we have very good estimate of >>> its range (say 0.7 >>> - 1.0). >>> >>> Now suppose instead of S02 (which i now set to a reasonable value), >>> I am interested in determining N, but it is highly correlated with >>> sigma2. Each time when disorder in the sample increases, the sigma2 >>> increases and due to its high correlation, N is also overestimated. >>> On the other hand, when the disorder in the sample decreases, the >>> sigma2 decreases and I can have a "true" estimation of N in the >>> sample. Can I still apply the above mentioned approach to break the correlationship between N and sigma2 and get a "true" >>> estimation of N, even if disorder is high in my samples ? or it is >>> simply not possible due to the fact that both N and sigma2 varies >>> with changes inside the sample. >> N and S02 are always 100% correlated (mathematically, not merely by the finite k range). So, to the extent that the approach works at all, you can use it for "N" or "S02". Really, the approach is comparing N*S02 and sigma2, in one case you asserted a value of "N" and projected all changes to "S02" -- you can equally assert "S02" and project all changes to "N". >> >> To be clear, this is not going to find the "true" value of anything, because no analysis is ever going to find the "true" value -- it's going to find a measured value. >> >> Finally, the correlation of N*S02 and sigma2 does not imply a bias in the values for N*S02. N*S02 is NOT overestimated because it is highly correlated with sigma2. >> >> Hope that helps, >> >> --Matt >> -------------- next part -------------- An HTML attachment was >> scrubbed... >> URL: >> <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/20150 >> 3 >> 22/86f5b809/attachment.html> >> >> ------------------------------ >> >> _______________________________________________ >> Ifeffit mailing list >> Ifeffit(a)millenia.cars.aps.anl.gov >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit >> >> >> End of Ifeffit Digest, Vol 145, Issue 40 >> **************************************** >> >> ________________________________ >> >> Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH >> >> Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. >> >> Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, >> stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph >> Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas >> Frederking >> >> Sitz Berlin, AG Charlottenburg, 89 HRB 5583 >> >> Postadresse: >> Hahn-Meitner-Platz 1 >> D-14109 Berlin >> >> http://www.helmholtz-berlin.de >> >> >> >> ------------------------------ >> >> _______________________________________________ >> Ifeffit mailing list >> Ifeffit(a)millenia.cars.aps.anl.gov >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit >> >> >> End of Ifeffit Digest, Vol 145, Issue 41 >> **************************************** >> >> ________________________________ >> >> Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH >> >> Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. >> >> Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, >> stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph >> Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas >> Frederking >> >> Sitz Berlin, AG Charlottenburg, 89 HRB 5583 >> >> Postadresse: >> Hahn-Meitner-Platz 1 >> D-14109 Berlin >> >> http://www.helmholtz-berlin.de >> >> _______________________________________________ >> Ifeffit mailing list >> Ifeffit(a)millenia.cars.aps.anl.gov >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > > > > ------------------------------ > > _______________________________________________ > Ifeffit mailing list > Ifeffit(a)millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > > > End of Ifeffit Digest, Vol 145, Issue 42 > **************************************** > > ________________________________ > > Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH > > Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. > > Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, > stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph > Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas > Frederking > > Sitz Berlin, AG Charlottenburg, 89 HRB 5583 > > Postadresse: > Hahn-Meitner-Platz 1 > D-14109 Berlin > > http://www.helmholtz-berlin.de > > _______________________________________________ > Ifeffit mailing list > Ifeffit(a)millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit ------------------------------ _______________________________________________ Ifeffit mailing list Ifeffit(a)millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit End of Ifeffit Digest, Vol 145, Issue 44 **************************************** ________________________________ Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas Frederking Sitz Berlin, AG Charlottenburg, 89 HRB 5583 Postadresse: Hahn-Meitner-Platz 1 D-14109 Berlin http://www.helmholtz-berlin.de ------------------------------ _______________________________________________ Ifeffit mailing list Ifeffit(a)millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit End of Ifeffit Digest, Vol 145, Issue 45 **************************************** ________________________________ Helmholtz-Zentrum Berlin für Materialien und Energie GmbH Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph Geschäftsführung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas Frederking Sitz Berlin, AG Charlottenburg, 89 HRB 5583 Postadresse: Hahn-Meitner-Platz 1 D-14109 Berlin http://www.helmholtz-berlin.de

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Re: [Ifeffit] Breaking down correlationships between parameters
by Rana, Jatinkumar Kantilal 23 Mar '15

23 Mar '15

Hi Scott, Thanks for your explanation. It means the reverse can also be true, i.e., I can guess N1 (nearest-neighbors in the first shell) and S02 by setting N2, N3 and N4 to values known from other analysis. I did a quick check by fitting the data. I conducted two fits: 1) setting S02 and guessing only N1 2) guessing both N1 and S02. To my surprise, both the fits gave very similar results, except that the fit#1 refined value of N1 to a higher side, while fit#2 estimated N1 closer to a physically reasonable value (as expected). I always constrained S02 when refining N for any path, due to 100% correlation between them. However, I am surprised to know that they can be refined independently. Best regards, Jatin -----Original Message----- From: ifeffit-bounces(a)millenia.cars.aps.anl.gov [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of ifeffit-request(a)millenia.cars.aps.anl.gov Sent: 23 March, 2015 14:19 To: ifeffit(a)millenia.cars.aps.anl.gov Subject: Ifeffit Digest, Vol 145, Issue 44 Send Ifeffit mailing list submissions to ifeffit(a)millenia.cars.aps.anl.gov To subscribe or unsubscribe via the World Wide Web, visit http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit or, via email, send a message with subject or body 'help' to ifeffit-request(a)millenia.cars.aps.anl.gov You can reach the person managing the list at ifeffit-owner(a)millenia.cars.aps.anl.gov When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." Today's Topics: 1. Re: Breaking down correlationships between parameters (Scott Calvin) ---------------------------------------------------------------------- Message: 1 Date: Mon, 23 Mar 2015 09:18:21 -0400 From: Scott Calvin <scalvin(a)sarahlawrence.edu> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> Subject: Re: [Ifeffit] Breaking down correlationships between parameters Message-ID: <78C1636C-91CF-4C8C-9D48-3EC361BB7237(a)slc.edu> Content-Type: text/plain; charset="utf-8" Hi Jatin, The key is that S02 should be the same for all paths. For example: Suppose you are very confident path 1 has a coordination number of 6, because of prior knowledge you have about the system. Paths 2, 3, and 4 have unknown coordination numbers, however. N1 (i.e. the degeneracy of path 1) you set to 6. You guess S02, N2, N3, and N4. Of course, the way Artemis and Ifeffit implement that, you're writing N1*S02 for the S02 field of Path 1, N2*S02 for the S02 field of Path 2, etc., and then setting N1 = 6 and guessing S02, N2, N3, and N4. There is now enough information for S02, N2, N3, and N4 to each be fitted without 100% correlation. ?Scott Calvin Sarah Lawrence College > On Mar 23, 2015, at 8:54 AM, Rana, Jatinkumar Kantilal <jatinkumar.rana(a)helmholtz-berlin.de> wrote: > > Hi Chris, > > The term N*S02 is fitted for each path of the FEFF calculation. So my question is, even if we know N with a great certainty for some path, how can we vary both N and S02 for other paths ? or Did I understand it wrong ? > > Best regards, > Jatin > > -----Original Message----- > From: ifeffit-bounces(a)millenia.cars.aps.anl.gov > [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of > ifeffit-request(a)millenia.cars.aps.anl.gov > Sent: 23 March, 2015 12:16 > To: ifeffit(a)millenia.cars.aps.anl.gov > Subject: Ifeffit Digest, Vol 145, Issue 42 > > Send Ifeffit mailing list submissions to > ifeffit(a)millenia.cars.aps.anl.gov > > To subscribe or unsubscribe via the World Wide Web, visit > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > or, via email, send a message with subject or body 'help' to > ifeffit-request(a)millenia.cars.aps.anl.gov > > You can reach the person managing the list at > ifeffit-owner(a)millenia.cars.aps.anl.gov > > When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." > > > Today's Topics: > > 1. Re: Breaking down correlationships between parameters > (Rana, Jatinkumar Kantilal) > 2. Re: Breaking down correlationships between parameters > (Chris Patridge) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Mon, 23 Mar 2015 11:00:19 +0000 > From: "Rana, Jatinkumar Kantilal" > <jatinkumar.rana(a)helmholtz-berlin.de> > To: "ifeffit(a)millenia.cars.aps.anl.gov" > <ifeffit(a)millenia.cars.aps.anl.gov> > Subject: Re: [Ifeffit] Breaking down correlationships between > parameters > Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE777@didag1> > Content-Type: text/plain; charset="utf-8" > > Hi Scott, > > Thank you for your comments. Can you please elaborate a little bit more on this "In cases like that, both N for all paths but one and S02 can be fit without 100% correlation." > > Best regards, > Jatin > > -----Original Message----- > From: ifeffit-bounces(a)millenia.cars.aps.anl.gov > [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of > ifeffit-request(a)millenia.cars.aps.anl.gov > Sent: 23 March, 2015 10:16 > To: ifeffit(a)millenia.cars.aps.anl.gov > Subject: Ifeffit Digest, Vol 145, Issue 41 > > Send Ifeffit mailing list submissions to > ifeffit(a)millenia.cars.aps.anl.gov > > To subscribe or unsubscribe via the World Wide Web, visit > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > or, via email, send a message with subject or body 'help' to > ifeffit-request(a)millenia.cars.aps.anl.gov > > You can reach the person managing the list at > ifeffit-owner(a)millenia.cars.aps.anl.gov > > When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." > > > Today's Topics: > > 1. Re: Breaking down correlationships between parameters > (Scott Calvin) > 2. Re: Breaking down correlationships between parameters > (Matt Newville) > 3. Re: Breaking down correlationships between parameters > (Rana, Jatinkumar Kantilal) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Sun, 22 Mar 2015 13:44:28 -0400 > From: Scott Calvin <scalvin(a)sarahlawrence.edu> > To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> > Subject: Re: [Ifeffit] Breaking down correlationships between > parameters > Message-ID: <E0C66911-7AD2-448C-9F64-F03E262D04D7(a)slc.edu> > Content-Type: text/plain; charset="utf-8" > > One side-comment from me: > > On Mar 22, 2015, at 12:52 PM, Matt Newville <newville(a)cars.uchicago.edu<mailto:newville@cars.uchicago.edu>> wrote: > > N and S02 are always 100% correlated (mathematically, not merely by the finite k range). > > Matt is saying that N and S02 are always 100% correlated for a single path. But in some situations you might know N for one path but not others. For example, you might know that the absorbing atom is octahedrally coordinated to oxygen but not be as certain as to next-nearest neighbors, or that there are copper atoms on the corners of a simple cubic lattice with a mixture of atoms at other positions. In cases like that, both N for all paths but one and S02 can be fit without 100% correlation. > > The degeneracy of multiple-scattering paths can often be constrained in terms of the coordination numbers for direct-scattering paths, which can further reduce (not ?break?) the correlation. > > In terms of the main question, I agree with Matt: I don?t think there?s much point in using the line-crossing technique nowadays; fitting using multiple k-weights simultaneously accomplishes the same thing but is a bit easier to interpret statistically. > > ?Scott Calvin > Sarah Lawrence College > -------------- next part -------------- An HTML attachment was > scrubbed... > URL: > <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/201503 > 22/f4e7b7e4/attachment-0001.htm> > > ------------------------------ > > Message: 2 > Date: Sun, 22 Mar 2015 15:56:20 -0500 > From: Matt Newville <newville(a)cars.uchicago.edu> > To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> > Subject: Re: [Ifeffit] Breaking down correlationships between > parameters > Message-ID: > > <CA+7ESbq_s0X3L9rPDDnwAdhx7h6Ptx5-8guCUFTM2OjwkYEerA(a)mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > > On Sun, Mar 22, 2015 at 12:44 PM, Scott Calvin > <scalvin(a)sarahlawrence.edu> > wrote: > >> One side-comment from me: >> >> On Mar 22, 2015, at 12:52 PM, Matt Newville >> <newville(a)cars.uchicago.edu> >> wrote: >> >> N and S02 are always 100% correlated (mathematically, not merely by >> the finite k range). >> >> >> Matt is saying that N and S02 are always 100% correlated *for a >> single path*. But in some situations you might know N for one path >> but not others. For example, you might know that the absorbing atom >> is octahedrally coordinated to oxygen but not be as certain as to >> next-nearest neighbors, or that there are copper atoms on the corners >> of a simple cubic lattice with a mixture of atoms at other positions. >> In cases like that, both N for all paths but one and S02 can be fit without 100% correlation. >> >> > Yes, I completely agree with Scott -- this is a good point that I > neglected. In addition to looking at multiple shells, one might also > consider using temperature or pressure dependence to separate N*S02 and > sigma2. Those aren't without assumptions, and still don't remove the > inherent correlation, but are useful approaches. > > The degeneracy of multiple-scattering paths can often be constrained > in >> terms of the coordination numbers for direct-scattering paths, which >> can further reduce (not ?break?) the correlation. >> >> In terms of the main question, I agree with Matt: I don?t think >> there?s much point in using the line-crossing technique nowadays; >> fitting using multiple k-weights simultaneously accomplishes the same >> thing but is a bit easier to interpret statistically. >> >> ?Scott Calvin >> Sarah Lawrence College >> >> _______________________________________________ >> Ifeffit mailing list >> Ifeffit(a)millenia.cars.aps.anl.gov >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit >> >> > --Matt > -------------- next part -------------- An HTML attachment was > scrubbed... > URL: > <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/201503 > 22/3dd3f763/attachment-0001.htm> > > ------------------------------ > > Message: 3 > Date: Mon, 23 Mar 2015 09:16:02 +0000 > From: "Rana, Jatinkumar Kantilal" > <jatinkumar.rana(a)helmholtz-berlin.de> > To: "ifeffit(a)millenia.cars.aps.anl.gov" > <ifeffit(a)millenia.cars.aps.anl.gov> > Subject: Re: [Ifeffit] Breaking down correlationships between > parameters > Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE755@didag1> > Content-Type: text/plain; charset="utf-8" > > Hi Matt, > > Thank you very much for your detailed explanation. As you pointed out that this approach ignores the statistical significance of fits and assumes that all fits are "good" fits. Also, the point that this approach yields a value of the parameter which is only slightly less correlated with the other one, but not completely removes the correlation. It makes it really clear to me that how this approach works and what are the pros and cons. > > Well, I myself has never tried this approach of minimizing the correlation between N*S02 and sigma2, but I read a lot about it in the literature. With my limited knowledge about the method, I could not judge this approach, although I had my own doubts. > > I truly appreciate your efforts in providing me a deeper insight into this approach. > > Best regards, > Jatin > > -----Original Message----- > From: ifeffit-bounces(a)millenia.cars.aps.anl.gov > [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of > ifeffit-request(a)millenia.cars.aps.anl.gov > Sent: 22 March, 2015 18:00 > To: ifeffit(a)millenia.cars.aps.anl.gov > Subject: Ifeffit Digest, Vol 145, Issue 40 > > Send Ifeffit mailing list submissions to > ifeffit(a)millenia.cars.aps.anl.gov > > To subscribe or unsubscribe via the World Wide Web, visit > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > or, via email, send a message with subject or body 'help' to > ifeffit-request(a)millenia.cars.aps.anl.gov > > You can reach the person managing the list at > ifeffit-owner(a)millenia.cars.aps.anl.gov > > When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." > > > Today's Topics: > > 1. Re: Breaking down correlationships between parameters > (Matt Newville) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Sun, 22 Mar 2015 11:52:30 -0500 > From: Matt Newville <newville(a)cars.uchicago.edu> > To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> > Subject: Re: [Ifeffit] Breaking down correlationships between > parameters > Message-ID: > > <CA+7ESbqcyQHf9XUh2uhk=Lv09An7E9LXxqDTX-X6kRJHy9PFzw(a)mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > > Hi Jatin, > > > On Sat, Mar 21, 2015 at 10:41 AM, Rana, Jatinkumar Kantilal < jatinkumar.rana(a)helmholtz-berlin.de> wrote: > >> Hi Matt, >> >> Thanks a lot for your prompt reply. The method I am referring to is >> not the multiple k-weight fits by constraining N*S02. My apologies >> for not being clear enough. Let's do it again. I am actually >> referring to an approach where we take an advantage of a different >> k-dependence of various parameters to breakdown correlations between >> them. For example, S02 and sigma2. S02 is k-independent and Sigma2 has k^2 dependence. >> >> > Yes, I am familiar with this approach, and I understand that this is what you are using. What I am saying is that this does not work nearly as well as (sometimes) claimed, and is sort of cheating. It ignores the measures of statistical significance. > > In this case, to breakdown correlation between S02 and sigma2, > > > The correlation between N*S02 and sigma2 is inherent to the finite k-range of the EXAFS signal. It cannot be "broken", though it might be reduced. > > >> one can assume a series of S02 values and perform fits using a single >> k-weight each time (say k-weight 1,2 and 3) and record corresponding >> sigma2 values. > > Let us say for k-weight =1, a series of preset S02 values will result > in a >> series of corresponding sigma2 values refined in fits, which can be >> plotted as a straight line in sigma2 vs. S02 plot. > > > OK, one can fit sigma2 with a series of preset values on N*S02. That's fine. But it does NOT lead to an infinitely thin line of sigma2 vs. > N*S02. Each sigma2 value on that line has a width, corresponding to its > uncertainty. In fact, the line you produce nicely demonstrates and > measures the correlation of N*S02 and sigma2 as the slope of this line. > > >> Similar straight lines can be obtained for fits using k-weight = 2 >> and then 3. > > Now, these three lines may intersect at or near some point, which will >> determine the "true" value of parameters independent of k-weight. > > > The different lines (each with finite thickness) will give a *range of > values* for N*S02 and sigma2, not a single value. > > The biggest problem with this approach is that it ignores the relative goodness-of-fits (let's just assume that is 'chi-square' for the purpose of > this discussion) for the fits along these lines. Some fits are better > than others, and this approach completely ignores that fact, and equally importantly ignores the fact that there is a range of values for chi-square > that are consistent with "good". If you include these values, your > linear plot will become contours of chi-square as a function of N*S02 and > sigma2. And, yes, by using different k-weights and k-ranges and so on you > can get overlapping contour plots which may reduce the correlation a small amount when looked at as an ensemble. And you can find a best set of values for N*S02 and sigma2, but *each* of these will have an uncertainty. > > So, you can use this approach to find a good value for N*S02, but it is not breaking the correlation. You can do this by hand. Or you can just do a > fit with datasets with different k-weights and k-ranges. When you do this > as a fit, you will see that the correlation is still fairly large. > > Also, just to be clear, this is absolutely not a "true" value. It is a measured value. Not at all the same thing. > > One can then constrain S02 to a value obtained from the point of >> intersection of three lines and vary sigma2 in a fit. > > > Well, one can certainly set N*S02 to some value and fit sigma2. As I said earlier, this ignores the correlation of N*S02 and sigma2, but does not remove that correlation. > > >> In this particular case, however, the advantage is, S02 does not >> depend on changes inside sample and we have very good estimate of its >> range (say 0.7 >> - 1.0). >> >> Now suppose instead of S02 (which i now set to a reasonable value), I >> am interested in determining N, but it is highly correlated with >> sigma2. Each time when disorder in the sample increases, the sigma2 >> increases and due to its high correlation, N is also overestimated. >> On the other hand, when the disorder in the sample decreases, the >> sigma2 decreases and I can have a "true" estimation of N in the >> sample. Can I still apply the above mentioned approach to break the correlationship between N and sigma2 and get a "true" >> estimation of N, even if disorder is high in my samples ? or it is >> simply not possible due to the fact that both N and sigma2 varies >> with changes inside the sample. >> >> > N and S02 are always 100% correlated (mathematically, not merely by the finite k range). So, to the extent that the approach works at all, you can use it for "N" or "S02". Really, the approach is comparing N*S02 and sigma2, in one case you asserted a value of "N" and projected all changes to "S02" -- you can equally assert "S02" and project all changes to "N". > > To be clear, this is not going to find the "true" value of anything, because no analysis is ever going to find the "true" value -- it's going to find a measured value. > > Finally, the correlation of N*S02 and sigma2 does not imply a bias in the values for N*S02. N*S02 is NOT overestimated because it is highly correlated with sigma2. > > Hope that helps, > > --Matt > -------------- next part -------------- An HTML attachment was > scrubbed... > URL: > <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/201503 > 22/86f5b809/attachment.html> > > ------------------------------ > > _______________________________________________ > Ifeffit mailing list > Ifeffit(a)millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > > > End of Ifeffit Digest, Vol 145, Issue 40 > **************************************** > > ________________________________ > > Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH > > Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. > > Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, > stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph > Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas > Frederking > > Sitz Berlin, AG Charlottenburg, 89 HRB 5583 > > Postadresse: > Hahn-Meitner-Platz 1 > D-14109 Berlin > > http://www.helmholtz-berlin.de > > > > ------------------------------ > > _______________________________________________ > Ifeffit mailing list > Ifeffit(a)millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > > > End of Ifeffit Digest, Vol 145, Issue 41 > **************************************** > > ________________________________ > > Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH > > Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. > > Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, > stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph > Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas > Frederking > > Sitz Berlin, AG Charlottenburg, 89 HRB 5583 > > Postadresse: > Hahn-Meitner-Platz 1 > D-14109 Berlin > > http://www.helmholtz-berlin.de > > > > ------------------------------ > > Message: 2 > Date: Mon, 23 Mar 2015 07:15:05 -0400 > From: Chris Patridge <patridge(a)buffalo.edu> > To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> > Subject: Re: [Ifeffit] Breaking down correlationships between > parameters > Message-ID: <29942DF9-8043-424E-BDCC-9CA19EB4AC9B(a)buffalo.edu> > Content-Type: text/plain; charset=utf-8 > > I think Scott was pointing out that first neighbors may be known with high certainty and therefore you can set this value thereby removing it and slightly reducing the correlations. > > Chris > > Sent from my iPhone > >> On Mar 23, 2015, at 7:00 AM, Rana, Jatinkumar Kantilal <jatinkumar.rana(a)helmholtz-berlin.de> wrote: >> >> Hi Scott, >> >> Thank you for your comments. Can you please elaborate a little bit more on this "In cases like that, both N for all paths but one and S02 can be fit without 100% correlation." >> >> Best regards, >> Jatin >> >> -----Original Message----- >> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov >> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of >> ifeffit-request(a)millenia.cars.aps.anl.gov >> Sent: 23 March, 2015 10:16 >> To: ifeffit(a)millenia.cars.aps.anl.gov >> Subject: Ifeffit Digest, Vol 145, Issue 41 >> >> Send Ifeffit mailing list submissions to >> ifeffit(a)millenia.cars.aps.anl.gov >> >> To subscribe or unsubscribe via the World Wide Web, visit >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit >> or, via email, send a message with subject or body 'help' to >> ifeffit-request(a)millenia.cars.aps.anl.gov >> >> You can reach the person managing the list at >> ifeffit-owner(a)millenia.cars.aps.anl.gov >> >> When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." >> >> >> Today's Topics: >> >> 1. Re: Breaking down correlationships between parameters >> (Scott Calvin) >> 2. Re: Breaking down correlationships between parameters >> (Matt Newville) >> 3. Re: Breaking down correlationships between parameters >> (Rana, Jatinkumar Kantilal) >> >> >> --------------------------------------------------------------------- >> - >> >> Message: 1 >> Date: Sun, 22 Mar 2015 13:44:28 -0400 >> From: Scott Calvin <scalvin(a)sarahlawrence.edu> >> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> >> Subject: Re: [Ifeffit] Breaking down correlationships between >> parameters >> Message-ID: <E0C66911-7AD2-448C-9F64-F03E262D04D7(a)slc.edu> >> Content-Type: text/plain; charset="utf-8" >> >> One side-comment from me: >> >> On Mar 22, 2015, at 12:52 PM, Matt Newville <newville(a)cars.uchicago.edu<mailto:newville@cars.uchicago.edu>> wrote: >> >> N and S02 are always 100% correlated (mathematically, not merely by the finite k range). >> >> Matt is saying that N and S02 are always 100% correlated for a single path. But in some situations you might know N for one path but not others. For example, you might know that the absorbing atom is octahedrally coordinated to oxygen but not be as certain as to next-nearest neighbors, or that there are copper atoms on the corners of a simple cubic lattice with a mixture of atoms at other positions. In cases like that, both N for all paths but one and S02 can be fit without 100% correlation. >> >> The degeneracy of multiple-scattering paths can often be constrained in terms of the coordination numbers for direct-scattering paths, which can further reduce (not ?break?) the correlation. >> >> In terms of the main question, I agree with Matt: I don?t think there?s much point in using the line-crossing technique nowadays; fitting using multiple k-weights simultaneously accomplishes the same thing but is a bit easier to interpret statistically. >> >> ?Scott Calvin >> Sarah Lawrence College >> -------------- next part -------------- An HTML attachment was >> scrubbed... >> URL: >> <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/20150 >> 3 >> 22/f4e7b7e4/attachment-0001.htm> >> >> ------------------------------ >> >> Message: 2 >> Date: Sun, 22 Mar 2015 15:56:20 -0500 >> From: Matt Newville <newville(a)cars.uchicago.edu> >> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> >> Subject: Re: [Ifeffit] Breaking down correlationships between >> parameters >> Message-ID: >> >> <CA+7ESbq_s0X3L9rPDDnwAdhx7h6Ptx5-8guCUFTM2OjwkYEerA(a)mail.gmail.com> >> Content-Type: text/plain; charset="utf-8" >> >> On Sun, Mar 22, 2015 at 12:44 PM, Scott Calvin >> <scalvin(a)sarahlawrence.edu> >> wrote: >> >>> One side-comment from me: >>> >>> On Mar 22, 2015, at 12:52 PM, Matt Newville >>> <newville(a)cars.uchicago.edu> >>> wrote: >>> >>> N and S02 are always 100% correlated (mathematically, not merely by >>> the finite k range). >>> >>> >>> Matt is saying that N and S02 are always 100% correlated *for a >>> single path*. But in some situations you might know N for one path >>> but not others. For example, you might know that the absorbing atom >>> is octahedrally coordinated to oxygen but not be as certain as to >>> next-nearest neighbors, or that there are copper atoms on the >>> corners of a simple cubic lattice with a mixture of atoms at other positions. >>> In cases like that, both N for all paths but one and S02 can be fit without 100% correlation. >> Yes, I completely agree with Scott -- this is a good point that I >> neglected. In addition to looking at multiple shells, one might also >> consider using temperature or pressure dependence to separate N*S02 and >> sigma2. Those aren't without assumptions, and still don't remove the >> inherent correlation, but are useful approaches. >> >> The degeneracy of multiple-scattering paths can often be constrained >> in >>> terms of the coordination numbers for direct-scattering paths, which >>> can further reduce (not ?break?) the correlation. >>> >>> In terms of the main question, I agree with Matt: I don?t think >>> there?s much point in using the line-crossing technique nowadays; >>> fitting using multiple k-weights simultaneously accomplishes the >>> same thing but is a bit easier to interpret statistically. >>> >>> ?Scott Calvin >>> Sarah Lawrence College >>> >>> _______________________________________________ >>> Ifeffit mailing list >>> Ifeffit(a)millenia.cars.aps.anl.gov >>> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit >> --Matt >> -------------- next part -------------- An HTML attachment was >> scrubbed... >> URL: >> <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/20150 >> 3 >> 22/3dd3f763/attachment-0001.htm> >> >> ------------------------------ >> >> Message: 3 >> Date: Mon, 23 Mar 2015 09:16:02 +0000 >> From: "Rana, Jatinkumar Kantilal" >> <jatinkumar.rana(a)helmholtz-berlin.de> >> To: "ifeffit(a)millenia.cars.aps.anl.gov" >> <ifeffit(a)millenia.cars.aps.anl.gov> >> Subject: Re: [Ifeffit] Breaking down correlationships between >> parameters >> Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE755@didag1> >> Content-Type: text/plain; charset="utf-8" >> >> Hi Matt, >> >> Thank you very much for your detailed explanation. As you pointed out that this approach ignores the statistical significance of fits and assumes that all fits are "good" fits. Also, the point that this approach yields a value of the parameter which is only slightly less correlated with the other one, but not completely removes the correlation. It makes it really clear to me that how this approach works and what are the pros and cons. >> >> Well, I myself has never tried this approach of minimizing the correlation between N*S02 and sigma2, but I read a lot about it in the literature. With my limited knowledge about the method, I could not judge this approach, although I had my own doubts. >> >> I truly appreciate your efforts in providing me a deeper insight into this approach. >> >> Best regards, >> Jatin >> >> -----Original Message----- >> From: ifeffit-bounces(a)millenia.cars.aps.anl.gov >> [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of >> ifeffit-request(a)millenia.cars.aps.anl.gov >> Sent: 22 March, 2015 18:00 >> To: ifeffit(a)millenia.cars.aps.anl.gov >> Subject: Ifeffit Digest, Vol 145, Issue 40 >> >> Send Ifeffit mailing list submissions to >> ifeffit(a)millenia.cars.aps.anl.gov >> >> To subscribe or unsubscribe via the World Wide Web, visit >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit >> or, via email, send a message with subject or body 'help' to >> ifeffit-request(a)millenia.cars.aps.anl.gov >> >> You can reach the person managing the list at >> ifeffit-owner(a)millenia.cars.aps.anl.gov >> >> When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." >> >> >> Today's Topics: >> >> 1. Re: Breaking down correlationships between parameters >> (Matt Newville) >> >> >> --------------------------------------------------------------------- >> - >> >> Message: 1 >> Date: Sun, 22 Mar 2015 11:52:30 -0500 >> From: Matt Newville <newville(a)cars.uchicago.edu> >> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> >> Subject: Re: [Ifeffit] Breaking down correlationships between >> parameters >> Message-ID: >> >> <CA+7ESbqcyQHf9XUh2uhk=Lv09An7E9LXxqDTX-X6kRJHy9PFzw(a)mail.gmail.com> >> Content-Type: text/plain; charset="utf-8" >> >> Hi Jatin, >> >> >>> On Sat, Mar 21, 2015 at 10:41 AM, Rana, Jatinkumar Kantilal < jatinkumar.rana(a)helmholtz-berlin.de> wrote: >>> >>> Hi Matt, >>> >>> Thanks a lot for your prompt reply. The method I am referring to is >>> not the multiple k-weight fits by constraining N*S02. My apologies >>> for not being clear enough. Let's do it again. I am actually >>> referring to an approach where we take an advantage of a different >>> k-dependence of various parameters to breakdown correlations between >>> them. For example, S02 and sigma2. S02 is k-independent and Sigma2 has k^2 dependence. >> Yes, I am familiar with this approach, and I understand that this is what you are using. What I am saying is that this does not work nearly as well as (sometimes) claimed, and is sort of cheating. It ignores the measures of statistical significance. >> >> In this case, to breakdown correlation between S02 and sigma2, >> >> >> The correlation between N*S02 and sigma2 is inherent to the finite k-range of the EXAFS signal. It cannot be "broken", though it might be reduced. >> >> >>> one can assume a series of S02 values and perform fits using a >>> single k-weight each time (say k-weight 1,2 and 3) and record >>> corresponding >>> sigma2 values. >> >> Let us say for k-weight =1, a series of preset S02 values will result >> in a >>> series of corresponding sigma2 values refined in fits, which can be >>> plotted as a straight line in sigma2 vs. S02 plot. >> >> >> OK, one can fit sigma2 with a series of preset values on N*S02. That's fine. But it does NOT lead to an infinitely thin line of sigma2 vs. >> N*S02. Each sigma2 value on that line has a width, corresponding to its >> uncertainty. In fact, the line you produce nicely demonstrates and >> measures the correlation of N*S02 and sigma2 as the slope of this line. >> >> >>> Similar straight lines can be obtained for fits using k-weight = 2 >>> and then 3. >> >> Now, these three lines may intersect at or near some point, which >> will >>> determine the "true" value of parameters independent of k-weight. >> >> >> The different lines (each with finite thickness) will give a *range >> of >> values* for N*S02 and sigma2, not a single value. >> >> The biggest problem with this approach is that it ignores the relative goodness-of-fits (let's just assume that is 'chi-square' for the purpose of >> this discussion) for the fits along these lines. Some fits are better >> than others, and this approach completely ignores that fact, and equally importantly ignores the fact that there is a range of values for chi-square >> that are consistent with "good". If you include these values, your >> linear plot will become contours of chi-square as a function of N*S02 and >> sigma2. And, yes, by using different k-weights and k-ranges and so on you >> can get overlapping contour plots which may reduce the correlation a small amount when looked at as an ensemble. And you can find a best set of values for N*S02 and sigma2, but *each* of these will have an uncertainty. >> >> So, you can use this approach to find a good value for N*S02, but it is not breaking the correlation. You can do this by hand. Or you can just do a >> fit with datasets with different k-weights and k-ranges. When you do this >> as a fit, you will see that the correlation is still fairly large. >> >> Also, just to be clear, this is absolutely not a "true" value. It is a measured value. Not at all the same thing. >> >> One can then constrain S02 to a value obtained from the point of >>> intersection of three lines and vary sigma2 in a fit. >> >> >> Well, one can certainly set N*S02 to some value and fit sigma2. As I said earlier, this ignores the correlation of N*S02 and sigma2, but does not remove that correlation. >> >> >>> In this particular case, however, the advantage is, S02 does not >>> depend on changes inside sample and we have very good estimate of >>> its range (say 0.7 >>> - 1.0). >>> >>> Now suppose instead of S02 (which i now set to a reasonable value), >>> I am interested in determining N, but it is highly correlated with >>> sigma2. Each time when disorder in the sample increases, the sigma2 >>> increases and due to its high correlation, N is also overestimated. >>> On the other hand, when the disorder in the sample decreases, the >>> sigma2 decreases and I can have a "true" estimation of N in the >>> sample. Can I still apply the above mentioned approach to break the correlationship between N and sigma2 and get a "true" >>> estimation of N, even if disorder is high in my samples ? or it is >>> simply not possible due to the fact that both N and sigma2 varies >>> with changes inside the sample. >> N and S02 are always 100% correlated (mathematically, not merely by the finite k range). So, to the extent that the approach works at all, you can use it for "N" or "S02". Really, the approach is comparing N*S02 and sigma2, in one case you asserted a value of "N" and projected all changes to "S02" -- you can equally assert "S02" and project all changes to "N". >> >> To be clear, this is not going to find the "true" value of anything, because no analysis is ever going to find the "true" value -- it's going to find a measured value. >> >> Finally, the correlation of N*S02 and sigma2 does not imply a bias in the values for N*S02. N*S02 is NOT overestimated because it is highly correlated with sigma2. >> >> Hope that helps, >> >> --Matt >> -------------- next part -------------- An HTML attachment was >> scrubbed... >> URL: >> <http://millenia.cars.aps.anl.gov/pipermail/ifeffit/attachments/20150 >> 3 >> 22/86f5b809/attachment.html> >> >> ------------------------------ >> >> _______________________________________________ >> Ifeffit mailing list >> Ifeffit(a)millenia.cars.aps.anl.gov >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit >> >> >> End of Ifeffit Digest, Vol 145, Issue 40 >> **************************************** >> >> ________________________________ >> >> Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH >> >> Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. >> >> Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, >> stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph >> Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas >> Frederking >> >> Sitz Berlin, AG Charlottenburg, 89 HRB 5583 >> >> Postadresse: >> Hahn-Meitner-Platz 1 >> D-14109 Berlin >> >> http://www.helmholtz-berlin.de >> >> >> >> ------------------------------ >> >> _______________________________________________ >> Ifeffit mailing list >> Ifeffit(a)millenia.cars.aps.anl.gov >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit >> >> >> End of Ifeffit Digest, Vol 145, Issue 41 >> **************************************** >> >> ________________________________ >> >> Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH >> >> Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. >> >> Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, >> stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph >> Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas >> Frederking >> >> Sitz Berlin, AG Charlottenburg, 89 HRB 5583 >> >> Postadresse: >> Hahn-Meitner-Platz 1 >> D-14109 Berlin >> >> http://www.helmholtz-berlin.de >> >> _______________________________________________ >> Ifeffit mailing list >> Ifeffit(a)millenia.cars.aps.anl.gov >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > > > > ------------------------------ > > _______________________________________________ > Ifeffit mailing list > Ifeffit(a)millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > > > End of Ifeffit Digest, Vol 145, Issue 42 > **************************************** > > ________________________________ > > Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH > > Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. > > Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, > stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph > Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas > Frederking > > Sitz Berlin, AG Charlottenburg, 89 HRB 5583 > > Postadresse: > Hahn-Meitner-Platz 1 > D-14109 Berlin > > http://www.helmholtz-berlin.de > > _______________________________________________ > Ifeffit mailing list > Ifeffit(a)millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit ------------------------------ _______________________________________________ Ifeffit mailing list Ifeffit(a)millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit End of Ifeffit Digest, Vol 145, Issue 44 **************************************** ________________________________ Helmholtz-Zentrum Berlin für Materialien und Energie GmbH Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph Geschäftsführung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas Frederking Sitz Berlin, AG Charlottenburg, 89 HRB 5583 Postadresse: Hahn-Meitner-Platz 1 D-14109 Berlin http://www.helmholtz-berlin.de

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Re: [Ifeffit] Breaking down correlationships between parameters
by Rana, Jatinkumar Kantilal 23 Mar '15

23 Mar '15

Hi Chris, The term N*S02 is fitted for each path of the FEFF calculation. So my question is, even if we know N with a great certainty for some path, how can we vary both N and S02 for other paths ? or Did I understand it wrong ? Best regards, Jatin -----Original Message----- From: ifeffit-bounces(a)millenia.cars.aps.anl.gov [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of ifeffit-request(a)millenia.cars.aps.anl.gov Sent: 23 March, 2015 12:16 To: ifeffit(a)millenia.cars.aps.anl.gov Subject: Ifeffit Digest, Vol 145, Issue 42 Send Ifeffit mailing list submissions to ifeffit(a)millenia.cars.aps.anl.gov To subscribe or unsubscribe via the World Wide Web, visit http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit or, via email, send a message with subject or body 'help' to ifeffit-request(a)millenia.cars.aps.anl.gov You can reach the person managing the list at ifeffit-owner(a)millenia.cars.aps.anl.gov When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." Today's Topics: 1. Re: Breaking down correlationships between parameters (Rana, Jatinkumar Kantilal) 2. Re: Breaking down correlationships between parameters (Chris Patridge) ---------------------------------------------------------------------- Message: 1 Date: Mon, 23 Mar 2015 11:00:19 +0000 From: "Rana, Jatinkumar Kantilal" <jatinkumar.rana(a)helmholtz-berlin.de> To: "ifeffit(a)millenia.cars.aps.anl.gov" <ifeffit(a)millenia.cars.aps.anl.gov> Subject: Re: [Ifeffit] Breaking down correlationships between parameters Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE777@didag1> Content-Type: text/plain; charset="utf-8" Hi Scott, Thank you for your comments. Can you please elaborate a little bit more on this "In cases like that, both N for all paths but one and S02 can be fit without 100% correlation." Best regards, Jatin -----Original Message----- From: ifeffit-bounces(a)millenia.cars.aps.anl.gov [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of ifeffit-request(a)millenia.cars.aps.anl.gov Sent: 23 March, 2015 10:16 To: ifeffit(a)millenia.cars.aps.anl.gov Subject: Ifeffit Digest, Vol 145, Issue 41 Send Ifeffit mailing list submissions to ifeffit(a)millenia.cars.aps.anl.gov To subscribe or unsubscribe via the World Wide Web, visit http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit or, via email, send a message with subject or body 'help' to ifeffit-request(a)millenia.cars.aps.anl.gov You can reach the person managing the list at ifeffit-owner(a)millenia.cars.aps.anl.gov When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." Today's Topics: 1. Re: Breaking down correlationships between parameters (Scott Calvin) 2. Re: Breaking down correlationships between parameters (Matt Newville) 3. Re: Breaking down correlationships between parameters (Rana, Jatinkumar Kantilal) ---------------------------------------------------------------------- Message: 1 Date: Sun, 22 Mar 2015 13:44:28 -0400 From: Scott Calvin <scalvin(a)sarahlawrence.edu> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> Subject: Re: [Ifeffit] Breaking down correlationships between parameters Message-ID: <E0C66911-7AD2-448C-9F64-F03E262D04D7(a)slc.edu> Content-Type: text/plain; charset="utf-8" One side-comment from me: On Mar 22, 2015, at 12:52 PM, Matt Newville <newville(a)cars.uchicago.edu<mailto:newville@cars.uchicago.edu>> wrote: N and S02 are always 100% correlated (mathematically, not merely by the finite k range). Matt is saying that N and S02 are always 100% correlated for a single path. But in some situations you might know N for one path but not others. For example, you might know that the absorbing atom is octahedrally coordinated to oxygen but not be as certain as to next-nearest neighbors, or that there are copper atoms on the corners of a simple cubic lattice with a mixture of atoms at other positions. In cases like that, both N for all paths but one and S02 can be fit without 100% correlation. The degeneracy of multiple-scattering paths can often be constrained in terms of the coordination numbers for direct-scattering paths, which can further reduce (not ?break?) the correlation. In terms of the main question, I agree with Matt: I don?t think there?s much point in using the line-crossing technique nowadays; fitting using multiple k-weights simultaneously accomplishes the same thing but is a bit easier to interpret statistically. ?Scott Calvin Sarah Lawrence College

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Re: [Ifeffit] Breaking down correlationships between parameters
by Rana, Jatinkumar Kantilal 23 Mar '15

23 Mar '15

Hi Scott, Thank you for your comments. Can you please elaborate a little bit more on this "In cases like that, both N for all paths but one and S02 can be fit without 100% correlation." Best regards, Jatin -----Original Message----- From: ifeffit-bounces(a)millenia.cars.aps.anl.gov [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of ifeffit-request(a)millenia.cars.aps.anl.gov Sent: 23 March, 2015 10:16 To: ifeffit(a)millenia.cars.aps.anl.gov Subject: Ifeffit Digest, Vol 145, Issue 41 Send Ifeffit mailing list submissions to ifeffit(a)millenia.cars.aps.anl.gov To subscribe or unsubscribe via the World Wide Web, visit http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit or, via email, send a message with subject or body 'help' to ifeffit-request(a)millenia.cars.aps.anl.gov You can reach the person managing the list at ifeffit-owner(a)millenia.cars.aps.anl.gov When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." Today's Topics: 1. Re: Breaking down correlationships between parameters (Scott Calvin) 2. Re: Breaking down correlationships between parameters (Matt Newville) 3. Re: Breaking down correlationships between parameters (Rana, Jatinkumar Kantilal) ---------------------------------------------------------------------- Message: 1 Date: Sun, 22 Mar 2015 13:44:28 -0400 From: Scott Calvin <scalvin(a)sarahlawrence.edu> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> Subject: Re: [Ifeffit] Breaking down correlationships between parameters Message-ID: <E0C66911-7AD2-448C-9F64-F03E262D04D7(a)slc.edu> Content-Type: text/plain; charset="utf-8" One side-comment from me: On Mar 22, 2015, at 12:52 PM, Matt Newville <newville(a)cars.uchicago.edu<mailto:newville@cars.uchicago.edu>> wrote: N and S02 are always 100% correlated (mathematically, not merely by the finite k range). Matt is saying that N and S02 are always 100% correlated for a single path. But in some situations you might know N for one path but not others. For example, you might know that the absorbing atom is octahedrally coordinated to oxygen but not be as certain as to next-nearest neighbors, or that there are copper atoms on the corners of a simple cubic lattice with a mixture of atoms at other positions. In cases like that, both N for all paths but one and S02 can be fit without 100% correlation. The degeneracy of multiple-scattering paths can often be constrained in terms of the coordination numbers for direct-scattering paths, which can further reduce (not ?break?) the correlation. In terms of the main question, I agree with Matt: I don?t think there?s much point in using the line-crossing technique nowadays; fitting using multiple k-weights simultaneously accomplishes the same thing but is a bit easier to interpret statistically. ?Scott Calvin Sarah Lawrence College

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Re: [Ifeffit] Breaking down correlationships between parameters
by Rana, Jatinkumar Kantilal 23 Mar '15

23 Mar '15

Hi Matt, Thank you very much for your detailed explanation. As you pointed out that this approach ignores the statistical significance of fits and assumes that all fits are "good" fits. Also, the point that this approach yields a value of the parameter which is only slightly less correlated with the other one, but not completely removes the correlation. It makes it really clear to me that how this approach works and what are the pros and cons. Well, I myself has never tried this approach of minimizing the correlation between N*S02 and sigma2, but I read a lot about it in the literature. With my limited knowledge about the method, I could not judge this approach, although I had my own doubts. I truly appreciate your efforts in providing me a deeper insight into this approach. Best regards, Jatin -----Original Message----- From: ifeffit-bounces(a)millenia.cars.aps.anl.gov [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of ifeffit-request(a)millenia.cars.aps.anl.gov Sent: 22 March, 2015 18:00 To: ifeffit(a)millenia.cars.aps.anl.gov Subject: Ifeffit Digest, Vol 145, Issue 40 Send Ifeffit mailing list submissions to ifeffit(a)millenia.cars.aps.anl.gov To subscribe or unsubscribe via the World Wide Web, visit http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit or, via email, send a message with subject or body 'help' to ifeffit-request(a)millenia.cars.aps.anl.gov You can reach the person managing the list at ifeffit-owner(a)millenia.cars.aps.anl.gov When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." Today's Topics: 1. Re: Breaking down correlationships between parameters (Matt Newville) ---------------------------------------------------------------------- Message: 1 Date: Sun, 22 Mar 2015 11:52:30 -0500 From: Matt Newville <newville(a)cars.uchicago.edu> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> Subject: Re: [Ifeffit] Breaking down correlationships between parameters Message-ID: <CA+7ESbqcyQHf9XUh2uhk=Lv09An7E9LXxqDTX-X6kRJHy9PFzw(a)mail.gmail.com> Content-Type: text/plain; charset="utf-8" Hi Jatin, On Sat, Mar 21, 2015 at 10:41 AM, Rana, Jatinkumar Kantilal < jatinkumar.rana(a)helmholtz-berlin.de> wrote: > Hi Matt, > > Thanks a lot for your prompt reply. The method I am referring to is > not the multiple k-weight fits by constraining N*S02. My apologies for > not being clear enough. Let's do it again. I am actually referring to > an approach where we take an advantage of a different k-dependence of > various parameters to breakdown correlations between them. For > example, S02 and sigma2. S02 is k-independent and Sigma2 has k^2 dependence. > > Yes, I am familiar with this approach, and I understand that this is what you are using. What I am saying is that this does not work nearly as well as (sometimes) claimed, and is sort of cheating. It ignores the measures of statistical significance. In this case, to breakdown correlation between S02 and sigma2, The correlation between N*S02 and sigma2 is inherent to the finite k-range of the EXAFS signal. It cannot be "broken", though it might be reduced. > one can assume a series of S02 values and perform fits using a single > k-weight each time (say k-weight 1,2 and 3) and record corresponding > sigma2 values. Let us say for k-weight =1, a series of preset S02 values will result in a > series of corresponding sigma2 values refined in fits, which can be > plotted as a straight line in sigma2 vs. S02 plot. OK, one can fit sigma2 with a series of preset values on N*S02. That's fine. But it does NOT lead to an infinitely thin line of sigma2 vs. N*S02. Each sigma2 value on that line has a width, corresponding to its uncertainty. In fact, the line you produce nicely demonstrates and measures the correlation of N*S02 and sigma2 as the slope of this line. > Similar straight lines can be obtained for fits using k-weight = 2 and > then 3. Now, these three lines may intersect at or near some point, which will > determine the "true" value of parameters independent of k-weight. The different lines (each with finite thickness) will give a *range of values* for N*S02 and sigma2, not a single value. The biggest problem with this approach is that it ignores the relative goodness-of-fits (let's just assume that is 'chi-square' for the purpose of this discussion) for the fits along these lines. Some fits are better than others, and this approach completely ignores that fact, and equally importantly ignores the fact that there is a range of values for chi-square that are consistent with "good". If you include these values, your linear plot will become contours of chi-square as a function of N*S02 and sigma2. And, yes, by using different k-weights and k-ranges and so on you can get overlapping contour plots which may reduce the correlation a small amount when looked at as an ensemble. And you can find a best set of values for N*S02 and sigma2, but *each* of these will have an uncertainty. So, you can use this approach to find a good value for N*S02, but it is not breaking the correlation. You can do this by hand. Or you can just do a fit with datasets with different k-weights and k-ranges. When you do this as a fit, you will see that the correlation is still fairly large. Also, just to be clear, this is absolutely not a "true" value. It is a measured value. Not at all the same thing. One can then constrain S02 to a value obtained from the point of > intersection of three lines and vary sigma2 in a fit. Well, one can certainly set N*S02 to some value and fit sigma2. As I said earlier, this ignores the correlation of N*S02 and sigma2, but does not remove that correlation. > In this particular case, however, the advantage is, S02 does not > depend on changes inside sample and we have very good estimate of its > range (say 0.7 > - 1.0). > > Now suppose instead of S02 (which i now set to a reasonable value), I > am interested in determining N, but it is highly correlated with > sigma2. Each time when disorder in the sample increases, the sigma2 > increases and due to its high correlation, N is also overestimated. On > the other hand, when the disorder in the sample decreases, the sigma2 > decreases and I can have a "true" estimation of N in the sample. Can I > still apply the above mentioned approach to break the correlationship between N and sigma2 and get a "true" > estimation of N, even if disorder is high in my samples ? or it is > simply not possible due to the fact that both N and sigma2 varies with > changes inside the sample. > > N and S02 are always 100% correlated (mathematically, not merely by the finite k range). So, to the extent that the approach works at all, you can use it for "N" or "S02". Really, the approach is comparing N*S02 and sigma2, in one case you asserted a value of "N" and projected all changes to "S02" -- you can equally assert "S02" and project all changes to "N". To be clear, this is not going to find the "true" value of anything, because no analysis is ever going to find the "true" value -- it's going to find a measured value. Finally, the correlation of N*S02 and sigma2 does not imply a bias in the values for N*S02. N*S02 is NOT overestimated because it is highly correlated with sigma2. Hope that helps, --Matt

1 0

Re: [Ifeffit] Breaking down correlationships between parameters
by Rana, Jatinkumar Kantilal 22 Mar '15

22 Mar '15

Hi Matt, Thanks a lot for your prompt reply. The method I am referring to is not the multiple k-weight fits by constraining N*S02. My apologies for not being clear enough. Let's do it again. I am actually referring to an approach where we take an advantage of a different k-dependence of various parameters to breakdown correlations between them. For example, S02 and sigma2. S02 is k-independent and Sigma2 has k^2 dependence. In this case, to breakdown correlation between S02 and sigma2, one can assume a series of S02 values and perform fits using a single k-weight each time (say k-weight 1,2 and 3) and record corresponding sigma2 values. Let us say for k-weight =1, a series of preset S02 values will result in a series of corresponding sigma2 values refined in fits, which can be plotted as a straight line in sigma2 vs. S02 plot. Similar straight lines can be obtained for fits using k-weight = 2 and then 3. Now, these three lines may intersect at or near some point, which will determine the "true" value of parameters independent of k-weight. One can then constrain S02 to a value obtained from the point of intersection of three lines and vary sigma2 in a fit. In this particular case, however, the advantage is, S02 does not depend on changes inside sample and we have very good estimate of its range (say 0.7 - 1.0). Now suppose instead of S02 (which i now set to a reasonable value), I am interested in determining N, but it is highly correlated with sigma2. Each time when disorder in the sample increases, the sigma2 increases and due to its high correlation, N is also overestimated. On the other hand, when the disorder in the sample decreases, the sigma2 decreases and I can have a "true" estimation of N in the sample. Can I still apply the above mentioned approach to break the correlationship between N and sigma2 and get a "true" estimation of N, even if disorder is high in my samples ? or it is simply not possible due to the fact that both N and sigma2 varies with changes inside the sample. Best regards, Jatin ________________________________________ From: ifeffit-bounces(a)millenia.cars.aps.anl.gov [ifeffit-bounces(a)millenia.cars.aps.anl.gov] on behalf of ifeffit-request(a)millenia.cars.aps.anl.gov [ifeffit-request(a)millenia.cars.aps.anl.gov] Sent: Saturday, March 21, 2015 3:14 PM To: ifeffit(a)millenia.cars.aps.anl.gov Subject: Ifeffit Digest, Vol 145, Issue 38 Send Ifeffit mailing list submissions to ifeffit(a)millenia.cars.aps.anl.gov To subscribe or unsubscribe via the World Wide Web, visit http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit or, via email, send a message with subject or body 'help' to ifeffit-request(a)millenia.cars.aps.anl.gov You can reach the person managing the list at ifeffit-owner(a)millenia.cars.aps.anl.gov When replying, please edit your Subject line so it is more specific than "Re: Contents of Ifeffit digest..." Today's Topics: 1. Re: amplitude parameter S02 larger than 1 (Scott Calvin) 2. Breaking down correlationships between parameters (Rana, Jatinkumar Kantilal) 3. Re: Breaking down correlationships between parameters (Matt Newville) ---------------------------------------------------------------------- Message: 1 Date: Fri, 20 Mar 2015 18:53:06 -0400 From: Scott Calvin <scalvin(a)sarahlawrence.edu> To: XAFS Analysis using Ifeffit <ifeffit(a)millenia.cars.aps.anl.gov> Subject: Re: [Ifeffit] amplitude parameter S02 larger than 1 Message-ID: <D2ADF788-9BC6-41E2-BD6B-794BD2E59DBC(a)slc.edu> Content-Type: text/plain; charset="utf-8" Hi Yanyun, Good. So here's the procedure for a Hamilton test. We're comparing the fit with S02 guessed to the one with S02 set to 0.90, because that was your a priori best guess at S02. I take the ratio of the first R-factor to the second. You didn't actually say the R-factor for the fit with S02 guessed, but it's clearly around 0.0055 based on the other information you gave. The R-factor for the 0.90 fit is 0.021. So the ratio is 0.0055/0.021 = 0.26, which we'll call x. For the first fit the degrees of freedom is 31.2 - 24 = 8.2. Take half of that and call that a. So a is 4.1. The first fit guesses 1 parameter that the second one doesn't. Take half of 1 and call that b. So b is 0.5. Find a regularized lower incomplete beta function calculator, like this one: http://www.danielsoper.com/statcalc3/calc.aspx?id=37 Enter x, a, and b. The result is 0.001. This means that there is a 0.1% chance that the fits are actually consistent, and that the difference is just due to noise in the data. So in this case, we can't just explain away the high S02 as insignificant. Of course, you could pretty much eyeball that once you gave me the uncertainties; since your fit said 1.45 +/- 0.14, that's likely to be quite incompatible with S02 = 0.9. Still, it's nice to put that on a firmer statistical basis, and I've personally found the Hamilton test quite helpful for answering "do I need to worry about [X]?" type questions. But in your case, you do need to worry about it. This discussion has generated several suggestions; hopefully one of them is a good lead! --Scott Calvin Sarah Lawrence College > On Mar 20, 2015, at 4:30 PM, huyanyun(a)physics.utoronto.ca wrote: > > Hi Scott, > > In all situations, 31.2 independent data points and 24 variables were > used. In the case of setting S02 to a value, 23 variables were used. > > Let me know if there is any other info needed. > > Best, > Yanyun > > > Quoting Scott Calvin <scalvin(a)sarahlawrence.edu>: > >> Hi Yanyun, >> >> To actually do a Hamilton test, the one other thing I need to know >> the number of degrees of freedom in the fit...if you provide that, >> I'll walk you through how to actually do a Hamilton test--it's not >> that bad, with the aid of an online calculator, and I think it might >> be instructive for some of the other people reading this list who >> are trying to learn EXAFS. >> >> --Scott Calvin >> Sarah Lawrence College >> >> >>> On Mar 20, 2015, at 3:46 PM, huyanyun(a)physics.utoronto.ca wrote: >>> >>> Hi Scott, >>> >>> Thank you so much for giving me your thought again. It is very helpful >>> to know how you and other XAFS experts deal with unusual situations. >>> >>> The floating S02 is fitted to be 1.45+/-0.14, this just means the fit >>> doesn't like the idea of an S02 in a typical range. Instead of setting >>> S02 to 0.9, I have to figure out why it happens and what it might >>> indicate. >>> >>> I guess a Hamilton test is done by adjusting one parameter (i.e., S02) >>> while keeping other conditions and model the same. Is that right? So >>> I record this test as following: >>> >>> 1) Floating S02: S02 fits to 1.45+/-0.14, R=0.0055, reduced >>> chi^2=17.86, Percentage=0.53+/-0.04 >>> 2) Set S02=0.7, R=0.044, reduced chi^2=120.6, percentage=0.81+/-0.2 >>> 3) set S02=0.8, R=0.030, reduced chi^2=86.10, percentage=0.77+/-0.07 >>> 3) set S02=0.9, R=0.021, reduced chi^2=60.16, percentage=0.72+/-0.06 >>> 4) set S02=1.0, R=0.017, reduced chi^2=49.5, percentage=0.67+/-0.05 >>> 5) set S02=1.1, R=0.012, reduced chi^2=35.1, percentage=0.62+/-0.03 >>> 6) set S02=1.2, R=0.009, reduced chi^2=24.9, percentage=0.59+/-0.02 >>> 7) set S02=1.3, R=0.007, reduced chi^2=18.9, percentage=0.57+/-0.02 >>> 8) set S02=1.4, R=0.0057, reduced chi^2=16.1, percentage=0.55+/-0.02 >>> 9) Floating S02 to be 1.45+/-0.14 >>> 10) set S02=1.6, R=0.006, reduced chi^2=17.8, percentage=0.53+/- 0.02 >>> 11) set S02=2.0, R=0.044, reduced chi^2=120.7, percentage=0.37+/-0.06. >>> >>> Therefore, I will say S02 falling in the range 1.2~1.6 gives >>> statistically improved fit, but S02=0.9 is not terrible as well. I >>> agree with you that I could always be confident to say the percentage >>> is 0.64+/-0.15, but I do want to shrink down the uncertainty and think >>> about other possibilities that could cause a large S02. >>> >>> I did double-check the data-reduction and normalization process. I >>> don't think I can improve anything in this step. By the way, I have a >>> series of similar samples and their fittings all shows floating S02 >>> larger than one based on the same two-sites model. >>> >>> Best, >>> Yanyun >>> >>> >>> >>> >>> Quoting Scott Calvin <scalvin(a)sarahlawrence.edu>: >>> >>>> Hi Yanyun, >>>> >>>> Lots of comments coming in now, so I?m editing this as I write it! >>>> >>>> One possibility for why you're getting a high best-fit S02 is that >>>> the fit doesn't care all that much about what the value of S02; i.e. >>>> there is broad range of S02's compatible with describing the fit as >>>> "good." That should be reflected in the uncertainty that Artemis >>>> reports. If S02 is 1.50 +/- 0.48, for example, that means the fit >>>> isn't all that "sure" what S02 should be. That would mean we could >>>> just shrug our shoulders and move on, except that it correlates with >>>> a parameter you are interested in (in this case, site occupancy). So >>>> in such a case, I think you can cautiously fall back on what might >>>> be called a "Bayesian prior"; i.e., the belief that the S02 should >>>> be "around" 0.9, and set the S02 to 0.9. (Or perhaps restrain S02 to >>>> 0.9; then you're really doing something a bit more like the notion >>>> of a Bayesian prior.) >>>> >>>> On the other hand, if the S02 is, say, 1.50 +/- 0.07, then the fit >>>> really doesn?t like the idea of an S02 in the typical range. An S02 >>>> that high, with that small an uncertainty, suggests to me that >>>> something is wrong?although it could be as simple as a normalization >>>> issue during data reduction. In that case, I?d be more skeptical of >>>> just setting S02 to 0.90 and going with that result; the fit is >>>> trying to tell you something, and it?s important to track down what >>>> that something is. >>>> >>>> Of course, once in a while, a fit will find a local minimum, while >>>> there?s another good local minimum around a more realistic value. >>>> That would be reflected by a fit that gave similarly good >>>> quantitative measures of fit quality (e.g. R-factors) when S02 is >>>> fit (and yields 1.50 +/- 0.07) as when its forced to 0.90. That?s >>>> somewhat unusual, however, particularly with a global parameter like >>>> S02. >>>> >>>> A good way to defend setting S02 to 0.90 is to use the Hamilton test >>>> to see if floating S02 yields a statistically significant >>>> improvement over forcing it to 0.90. If not, using your prior best >>>> estimate for S02 is reasonable. >>>> >>>> If you did that, though, I?d think that it would be good to mention >>>> what happened in any eventual publication of presentation; it might >>>> provide an important clue to someone who follows up with this or a >>>> similar system. It would also be good to increase your reported >>>> uncertainty for site occupancy (and indicate in the text what you?ve >>>> done). I now see that your site occupancies are 0.53 +/- 0.04 for >>>> the floated S02, and 0.72 +/-0.06 for the S02 = 0.90. That?s not so >>>> bad, really. It means that you?re pretty confident that the site >>>> occupancy is 0.64 +/- 0.15, which isn?t an absurdly large >>>> uncertainty as these things go. >>>> >>>> To be concrete, if all the Hamilton test does not show statistically >>>> significant improvement by floating S02, then I might write >>>> something like this in any eventual paper: ?The site occupancy was >>>> highly correlated with S02 in our fits, making it difficult to >>>> determine the site occupancy with high precision. If S02 is >>>> constrained to 0.90, a plausible value for element [X] [ref], then >>>> the site occupancy is 0.53 +/- 0.04. If constrained to 1.0, the site >>>> occupancy is [whatever it comes out to be] To reflect the increased >>>> uncertainty associated with the unknown value for S02, we are >>>> adopting a value of 0.53 +/- [enough uncertainty to cover the >>>> results found for S02 = 1.0]. >>>> >>>> Of course, if you do that, I?d also suggest tracking down as many >>>> other possibilities for why your fit is showing high values of S02 >>>> as you can; e.g., double-check your normalization during data >>>> reduction. >>>> >>>> If, on the other hand, the Hamilton test does show the floated S02 >>>> is yielding a statistically significant improvement, I think you >>>> have a bigger issue. Looking at, e.g., whether you may have >>>> constrained coordination numbers incorrectly becomes more critical. >>>> >>>> ?Scott Calvin >>>> Sarah Lawrence College >>>> >>>> >> >> >> _______________________________________________ >> Ifeffit mailing list >> Ifeffit(a)millenia.cars.aps.anl.gov >> http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit > > > > > _______________________________________________ > Ifeffit mailing list > Ifeffit(a)millenia.cars.aps.anl.gov > http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit ------------------------------ Message: 2 Date: Sat, 21 Mar 2015 13:06:39 +0000 From: "Rana, Jatinkumar Kantilal" <jatinkumar.rana(a)helmholtz-berlin.de> To: "ifeffit(a)millenia.cars.aps.anl.gov" <ifeffit(a)millenia.cars.aps.anl.gov> Subject: [Ifeffit] Breaking down correlationships between parameters Message-ID: <DA4C7D90F90BC249A03505C87F2EB8AB230EE6D1@didag1> Content-Type: text/plain; charset="iso-8859-1" Dear All, I have stumbled upon a question regarding correlationships between various parameters in EXAFS fitting. As we know, the parameters S02*N and sigma2 are highly correlated (where N is the number of nearest neighbors). I would like to determine the number of nearest neighbors for a series of sample subjected to some treatment. I can do this by simply setting S02 to a value for a given absorber (based on the literature or my own measurements of some reference compounds) and letting N and sigma2 vary in a fit. However, the problem is the physical process which changes the number of nearest neighbors, also introduces structural disorder in samples. Thus, I always get the values of N overestimated due to its correlationship with sigma2. I know of a method which can be used to breakdown the correlationship between S02 and sigma2 by setting a series of S02 values at different k-weights and refining the corresponding sigma2 as discussed in several literature. However, in this approach the explicit assumption is, S02 is the property of absorbing atoms and thus is independent of changes occurring inside the sample. In my case, however, both sigma2 and N vary with changes inside samples. Is there any way to break this correlationship ? I look forward to your valuable suggestions and comments. Best regards, Jatin ________________________________ Helmholtz-Zentrum Berlin f?r Materialien und Energie GmbH Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph Gesch?ftsf?hrung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas Frederking Sitz Berlin, AG Charlottenburg, 89 HRB 5583 Postadresse: Hahn-Meitner-Platz 1 D-14109 Berlin http://www.helmholtz-berlin.de

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Breaking down correlationships between parameters
by Rana, Jatinkumar Kantilal 21 Mar '15

21 Mar '15

Dear All, I have stumbled upon a question regarding correlationships between various parameters in EXAFS fitting. As we know, the parameters S02*N and sigma2 are highly correlated (where N is the number of nearest neighbors). I would like to determine the number of nearest neighbors for a series of sample subjected to some treatment. I can do this by simply setting S02 to a value for a given absorber (based on the literature or my own measurements of some reference compounds) and letting N and sigma2 vary in a fit. However, the problem is the physical process which changes the number of nearest neighbors, also introduces structural disorder in samples. Thus, I always get the values of N overestimated due to its correlationship with sigma2. I know of a method which can be used to breakdown the correlationship between S02 and sigma2 by setting a series of S02 values at different k-weights and refining the corresponding sigma2 as discussed in several literature. However, in this approach the explicit assumption is, S02 is the property of absorbing atoms and thus is independent of changes occurring inside the sample. In my case, however, both sigma2 and N vary with changes inside samples. Is there any way to break this correlationship ? I look forward to your valuable suggestions and comments. Best regards, Jatin ________________________________ Helmholtz-Zentrum Berlin für Materialien und Energie GmbH Mitglied der Hermann von Helmholtz-Gemeinschaft Deutscher Forschungszentren e.V. Aufsichtsrat: Vorsitzender Prof. Dr. Dr. h.c. mult. Joachim Treusch, stv. Vorsitzende Dr. Beatrix Vierkorn-Rudolph Geschäftsführung: Prof. Dr. Anke Rita Kaysser-Pyzalla, Thomas Frederking Sitz Berlin, AG Charlottenburg, 89 HRB 5583 Postadresse: Hahn-Meitner-Platz 1 D-14109 Berlin http://www.helmholtz-berlin.de

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