Hi,

This is quite a large task that would require a couple of months, but
it would mean that large scale screening of dispersion parameter
errors would have been possible.  What is your plan for the
est_par_error branch
(http://svn.gna.org/viewcvs/relax/branches/est_par_error/?pathrev=25575)?
 There are some useful things in there for the next developer to take
over - the new lib.dispersion.tsmfk01 gradient and Jacobian functions,
the sympy script for the partial derivatives, the TSMFK01 target
function class gradient methods, etc.

Regards,

Edward



On 2 September 2014 20:10, Troels E. Linnet
<[email protected]> wrote:
> Update of task #7824 (project relax):
>
>                 Priority:                 3 - Low => 1 - Later
>                   Status:             In Progress => Gone walkabout
>         Percent Complete:                      0% => 10%
>
>     _______________________________________________________
>
> Follow-up Comment #50:
>
> This is actually a quite hard work to implement, and will require a lot of
> testing.
>
> I therefore leave it, since I dont have time for it.
>
> But it seemed that it is very possible indeed.
>
> For the most simple model TSMFK01, reasonable results was achieved.
>
> But seriously, perform MC calculations in the end.
>
> Compared to R2eff errors, where the following analysis depend on the error,
> the error estimation for the model parameters can wait to the very last end.
> So it is not crucial.
>
>
>
>
>
>     _______________________________________________________
>
> Reply to this item at:
>
>   <http://gna.org/task/?7824>
>
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