Hi Edward.

I was through sor (sum of residuals), sos(sum of squares), and now sse(sum
of squared errors).

I agree with sse being the best, but I have reverted all my commits, and
found a solution through the API.

Just using the chi2 value, and finding degrees of freedom with the API.

If one wants .sse, one can just quickly do

value.set(val=1.0, param="r2eff", error=True)
minimise.calculate(verbosity=1)

Anyway, in the end, the new method did not solve my problem.
STD_fit = sqrt(chi2 / dof)

Since dof is so big (many datapoints, small amounts of parameters for
clustered fitting), STD_fit becomes close to 1.


Best
Troels


2015-01-19 9:35 GMT+01:00 Edward d'Auvergne <edw...@nmr-relax.com>:

> Hi Troels,
>
> Could you rename spin.sos to spin.sse?  This is the acronym used in
> the field and by other software - the sum of squared errors
> (https://en.wikipedia.org/wiki/Residual_sum_of_squares,
> http://www.palmer.hs.columbia.edu/software/modelfree_manual.pdf).  If
> the individual SSE elements are divided by the experimental error
> sigma_i, then this is the chi2 value.  The SSE and chi2 statistics are
> related, and are identical in the case of unit errors.  Other
> acronyms, much less used in the NMR field, are SSR or RSS.  I don't
> think I've ever encountered SOS before, outside of emergencies
> (https://en.wikipedia.org/wiki/SOS).
>
> Cheers,
>
> Edward
>
> On 16 January 2015 at 23:19,  <tlin...@nmr-relax.com> wrote:
> > Author: tlinnet
> > Date: Fri Jan 16 23:19:50 2015
> > New Revision: 27203
> >
> > URL: http://svn.gna.org/viewcvs/relax?rev=27203&view=rev
> > Log:
> > Implemented storing of sum of squares and the standard deviation of
> these for relaxation dispersion, when doing a point calculation.
> >
> > Task #7882 (https://gna.org/task/?7882): Implement Monte-Carlo
> simulation, where errors are generated with width of standard deviation or
> residuals.
> >
> > Modified:
> >     trunk/specific_analyses/relax_disp/optimisation.py
> >
> > Modified: trunk/specific_analyses/relax_disp/optimisation.py
> > URL:
> http://svn.gna.org/viewcvs/relax/trunk/specific_analyses/relax_disp/optimisation.py?rev=27203&r1=27202&r2=27203&view=diff
> >
> ==============================================================================
> > --- trunk/specific_analyses/relax_disp/optimisation.py  (original)
> > +++ trunk/specific_analyses/relax_disp/optimisation.py  Fri Jan 16
> 23:19:50 2015
> > @@ -119,7 +119,7 @@
> >      @type spin_lock_nu1:        list of lists of numpy rank-1 float
> arrays
> >      @keyword relax_times_new:   The interpolated experiment specific
> fixed time period for relaxation (in seconds).  The dimensions are {Ei, Mi,
> Oi, Di, Ti}.
> >      @type relax_times_new:      rank-4 list of floats
> > -    @keyword store_chi2:        A flag which if True will cause the
> spin specific chi-squared value to be stored in the spin container.
> > +    @keyword store_chi2:        A flag which if True will cause the
> spin specific chi-squared value to be stored in the spin container together
> with the sum of squares of the residuals and the standard deviation of the
> sum of squares of the residuals.
> >      @type store_chi2:           bool
> >      @return:                    The back-calculated R2eff/R1rho value
> for the given spin.
> >      @rtype:                     numpy rank-1 float array
> > @@ -215,10 +215,15 @@
> >      # Make a single function call.  This will cause back calculation
> and the data will be stored in the class instance.
> >      chi2 = model.func(param_vector)
> >
> > -    # Store the chi-squared value.
> > +    # Get the sum of squares 'sos' of the residuals between the fitted
> values and the measured values. Get the std deviation of these, std_sos.
> > +    sos, sos_std = model.get_sum_of_squares()
> > +
> > +    # Store the chi-squared value, sums of squares of residual and the
> standard deviation of sums of squares of residual.
> >      if store_chi2:
> >          for spin in spins:
> >              spin.chi2 = chi2
> > +            spin.sos = sos
> > +            spin.sos_std = sos_std
> >
> >      # Return the structure.
> >      return model.get_back_calc()
> >
> >
> > _______________________________________________
> > relax (http://www.nmr-relax.com)
> >
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> >
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>
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