[Ifeffit] bond distance resolution and correlation of parameters in MS analyses?

[Bruce Ravel]

On Wednesday 06 June 2007, MarkBondin wrote:
> 2) What is the actual equation which defines the determinacy of a fitting
> procedure and does this differ between SS and MS analyses? For MS analyses
> there has been a recently published equation (Coord. Chem. Rev. 2005, 249,
> 141-160) which takes into acount the number of dimensions used in the
> analyses and is this only relevant to MS analyses of data? This has also
> been expressed in the paper by Binsted (Biochemistry. 1992, 31,
> 12117-12125) however a different equation has been detailed by Stern (Phys.
> Rev. B. 1993, 48, 9825-9827) which I have been using as a guide in my MS
> analyses. Is this acceptable?


 1. I don't know what you mean by the word "determinacy".  In any
    case, I thought I made it clear in my last post that, in my
    opinion, the differences between SS and MS analysis are in the
    physical interpretation and not in the statistical interpretation.
    Feff, Ifeffit, and Artemis certainly go to great lengths to
    downplay the differences between SS and MS paths in the context of
    the formalism of the theory and analysis, instead emphasizing
    their differences only in the context of physical interpretation.

 2. Argonne's library only has access to the last year of
    Coord. Chem. Rev. and I don't have time this week to go fetch it
    from the stacks.  So I cannot comment on that paper.

 3. The paper by Stern should be read with some care.  The argument Ed
    makes in that paper can only be true in the case of a perfectly
    packed signal.  EXAFS data, although treated as signal processing
    problem, is never perfectly packed.  The Nyquist criterion is an
    upper bound on the information content, but the actual content of
    the data is always somewhat less.  There are some very fine papers
    by Rossner and Krappe about using Baysian techniques to find the
    actual information content of the EXAFS signal.  The executive
    summary is that if think you need Ed's magic "+2", you are
    probably overusing the information content of your data.

    Most of us here in this list aren't as careful in practice as all
    that Baysian stuff.  In general, one tries to stay "well below"
    the Nyquist upper bound.  If your fitting parameters make sense
    physically, if the correlations are not "too high", and if the
    error bars on your parameters are not "too big", then you are
    probably not overusing the information content of your data.

    What is "too high" and "too big"?  Well, I am purposefully using
    squishy language.  It is kind of difficult to use Gaussian
    statistical techniques on EXAFS data, despite the fact that that's
    exactly what Ifeffit does.  The reason is that Gaussin statistics
    presumes that your measurememt errors are statistical and normally
    distributed.  In practice, exafs analysis is dominated by
    systematic uncertainties.  Things like detector or sample
    non-linearities and the approximations made by Feff are much
    bigger sources of error than shot noise for most experiments.
    Most of those systematic problems are present in your analysis,
    but I have no idea how you could possibly quantify them.  Hence I
    find myself using squishy language to discuss fit statistics.

    Read the papers by the frequent contributors to this mailing
    list.  Scott Calvin and Shelly Kelly in particular are careful
    EXAFS practitioners who work on tough analysis problems and deal
    well with these issues.  Doing what they do may not be as right as
    possible, but it certainly ain't wrong.

HTH,
B


-- 
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