[Octave-bug-tracker] [bug #38063] optim: expfit inaccurate (incorrect)

[Olaf Till]

Follow-up Comment #5, bug #38063 (project octave):

Ok, I confirmed that nonlin_curvefit finds the parameters with suitable
initial values.

But now the situation, as I see it, is:

- little noise:

-- expfit finds the correct parameters

-- nonlin_residmin finds them, too, but only with suitable initial values
(since you don't know the correct parameters beforehand, this may be a
problem)

- much noise:

-- expfit does not find the correct parameters and not even a good fit

-- nonlin_residmin also does not find the correct parameters, but achieves a
good fit

So with little noise having expfit may be an advantage. With much (realistic?)
noise possibly nothing helps; except if you only want to fit, not to find the
parameters -- then you have to take a general optimizer.

In other words, if you need the correct parameters, not only the fit, you are
either at the loss due to much (realistic?) noise, or you should better use
expfit.

I still don't see how renaming expfit helps to clarify this situation.

It is a matter of ones emphasis how bad it is that expfit doesn't achieve a
good fit if it can't find the correct parameters anyway; maybe this is even a
feature of the algorithm (which I havn't checked). In life- (and probably
other) science, one is often concerned with finding the correct parameters of
a hopefully suitable model; if this isn't successful and a good fit is still
needed, one can still switch to a general optimizer. If you feel that expfit
should still give a good fit in this case, the right way is probably to check
whether the algorithm is principally able to provide this and make a
respective correction.

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