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Re: [Help-gsl] Re: Re: non-linear least squares fitting

From: Barrett C. Foat
Subject: Re: [Help-gsl] Re: Re: non-linear least squares fitting
Date: Thu, 6 Dec 2007 08:25:20 -0600
User-agent: KMail/1.9.3

I guess that I misunderstood. I have always used analytical partial 
derivatives. I am kind of surprised that numerical partial derivatives 
work. However, if the optimization converges without errors, it must be a 
good enough approximation for your function. In my experience, this 
package fails to converge if you do something wrong with the derivatives.

Barrett Foat

On Thursday 06 December 2007 03:21, Richard Henwood wrote:
> <posted & mailed>
> Barrett Foat wrote:
> >> I implement fdf using numerical partial differentiation of f.
> >>
> >> This method (numerical partial differentials) appeared to work;
> >> is this a reasonable approach?
> >
> > Yes, the df and fdf functions need to caluclate the numerical partial
> > derivatives given the current values of the arguments (vector x in the
> > docs) and your independent variable data.
> >
> > To my knowledge, the approach you took is the only reasonable
> > approach.
> Good.
> Is the only alternative approach to use the analytic partial derivatives
> in df and fdf?
> My reading is that this approach is used in the example given in the GSL
> manual example.
> r,
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