Hi Gabriel and Chales,
Thanks for the response.
@Gabriel : The percent deviation seems like a good indicator for most of
the RDC values except those very small RDC values. I am not sure if thats
the right metric over-all. In almost all the RDC's I am using, there seems
to be 1-2 RDC's of this small magnitude.
@Charles : Can you please elaborate a bit more about semi-quantitative
errors, |err| .. Is that the experimental observation errors ? or the RMS
between Experimental and calculated RDC's.
And also I have questions about modelling errors in RDC's. In the work you
have did, you used 0.26 HZ as the standard deviation for NH for synthetic
data, but when you have experimental data of magnitude 0.03 [less than the
standard deviation used in error modelling], is this approach still valid?
Thanks
santhosh
On Thu, Nov 14, 2013 at 10:00 AM, Charles Schwieters <char...@schwieters.org
> wrote:
>
> Hello Santhosh--
>
> >
> > To find how good a refinement is, R-factors or Q-factor is used as a
> general
> > broad indicator.
> >
> > R-factor defined as : sqrt{Sum[(Exp-obs)^2])/Sum[Exp^2]/2}
> >
> > This R-factor is a good indicator of the over-all data fit but is there
> any such
> > indicator for residue wise improvement. I tried residue wise R-factor as
> :
> >
> > Residue R-factor : |Exp - Obs| / |Exp|
> > [basically percent deviation].
> >
>
> Gabriel is correct that R-factor does take into account the magnitude
> of RDCs, but for a per-residue metric, if you have semi-quantitative
> errors, how about this residual:
>
> |Exp - Calcd| / |err|
>
> ??
>
> Charles
>
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