[Top][All Lists]

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Re: Non-Linear implicit Curve Fitting

From: Olaf Till
Subject: Re: Non-Linear implicit Curve Fitting
Date: Sat, 16 Nov 2013 22:52:42 +0100
User-agent: Mutt/1.5.21 (2010-09-15)

On Sat, Nov 16, 2013 at 08:54:45AM +0100, Christian Kascha wrote:
> Am 15.11.2013 18:22, schrieb Giftig:
> >Good Day
> >
> >I have two data sets.x and F that has about 10000 points each.
> >
> >I also have the following equation:
> >F = C_CV .* alpha.^( x - 1) .* sqrt(a .* F.^2+ b * F + c)
> >
> >I want to fit that equation on the data above. everything is unknown as
> >specified.
> >Any idea on how to accomplish this?
> >
> >I tried a few methods put nothing gave me a proper fit

What did you try?

> >Thank you
> I would try non-linear least squares with "fminsearch" or "fminunc"
> from the optim package.
> (
> Best,
> Christian

I think Giftig has not a scalar objective function, so its worth
trying residual minimization. Rearrange the equation to return zero
and use, e.g., nonlin_residmin of the optim package (this also fits to
least squares by default). But the fit is doubtful to be well defined
if 'C_CV' and 'a' are vectors, as they seem to be by your usage of
'.*' (more unknowns than residuals) (and the problem would probably be
too large in this case anyway).

If necessary, feel free to ask for specific details.


public key id EAFE0591, e.g. on x-hkp://

Attachment: signature.asc
Description: Digital signature

reply via email to

[Prev in Thread] Current Thread [Next in Thread]