[Ifeffit] Question about transform windows and statistical parameters

[Bruce Ravel]

On Wednesday, May 11, 2011 11:45:43 pm Brandon Reese wrote:
> Does this mean that reporting reduced chi-square values in a paper
> that compared several data sets would not be necessary and/or
> appropriate?

Heavens!  No!

That we don't have a reliable way of estimating epsilon says that we
cannot apply the standard criterion for recognizing a good fit
(i.e. in Gaussian statistics, a reduced chi-square of 1 indicates a
good fit).  That is, in Ifeffit/Artemis, reduced chi-square for a
single fit cannot be interpretted.

However, reduced chi-square can be used to assert that one fitting
model is an improvement on another fitting model.  If reduced
chi-square gets significantly smaller, then the second fitting model
can be said to be an improvement over the first.  So, if the point of
a paper is to say that your sample behaves *this* way and not *that*
way, one of the tools available to you for making that argument is
that the data are more consistent with *this* model because its
reduced chi-square is significantly smaller than for *that* model.

Of course, reduced chi-square can only be compared for fitting models
which compute epsilon the same way or use the same value for epsilon.

> Would setting a value for epsilon allow comparisons across different
> k-ranges, different (but similar) data sets, or a combination of the
> two using the [reduced] chi-square parameter?

Yup.  What you wrote wasn't strictly wrong, but considering the
reduced chi-square lets you also compare fits with different variable
parameters.

B


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