[SciPy-user] optimization question
Wed Jul 4 02:20:16 CDT 2007
> All leastsq() really adds to fmin*() is that you return the residuals
> instead of summing up the squares of the residuals. You can do that
> manually and use whichever minimizer you need.
Can you give me a short example, how to do so? I´ve asked this also
Matthieu, so if he will answer, you probably don´t need to. But two
examples would be better than one ;)
> Well, that's a big problem. You have twice as many variables to fit
as > you have datapoints. There are possibly an infinite number of
> solutions that exactly(!) fit your data.
I see, indeed i need as many datapoints (equations) as variables, to
solve the problem.
> Is it possible that you can reparameterize your problem? Perhaps c(.)
> and d(.)
> could be formulated as functions that depend on some small number of
> besides x_i in order to smooth things out. You would then do
> least-squares to optimize those parameters.
I think i can do that. There are some physical constraints for c(x_i)
and d(x_i), which should make it possible to reparameterize c an d.
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