On 11/1/06, Ines Hellmann <[EMAIL PROTECTED]> wrote:
I am using the gsl_multimin_fminimizer with the Nelder Mead ("ambeba")
algorithm and want to
put some constraints on the parameters that are optimized. Like I don't
want them to become negative.
Is there a way to do this and if so, what is it?
Brian,
Thanks for the reply. I will certainly apply what you are suggesting
Regards
Rene
Brian Gough <[EMAIL PROTECTED]> wrote: Rene Girard wrote:
> double g1(double, double *);
>
> I would like to bring to your attention that when I
> compile that simple example and
> I set the pointer to th
Hi,
I am using the gsl_multimin_fminimizer with the Nelder Mead ("ambeba")
algorithm and want to
put some constraints on the parameters that are optimized. Like I don't
want them to become negative.
Is there a way to do this and if so, what is it?
Thanx,
Ines
___
On 31/10/2006, at 10:42 PM, Fred J. wrote:
John Gehman <[EMAIL PROTECTED]> wrote:
I don't have the documentation handy at the moment, so just some
general
guidance ...
What you've done is a systematic search of all parameter space. And
even
though you've declared double type, you app
From: Petr Ent<[EMAIL PROTECTED]
Subject: [Help-gsl] fitting hi
everyone, is it possible to do following thing with non-linear least
squares fitting...?
double x_init[3] = { 1.0, 0.0, 0.0 }; gsl_vector_view x =
gsl_vector_view_array (x_init, p); T = gsl_multifit_fdfsolver_lmsder;
s = gsl_multi
hi everyone,
I have one more question about nonlinear least squares fitting, I will use the
example from GSL online manual. I copied it to my program and just changed the
equation to
y = Ai(1-exp(-t/ti)) + Ap(1-exp(-t/tp))
with parameters Ai, Ap, ti, tp
I set correct partial derivations too, t
> hi everyone,
> is it possible to do following thing with non-linear least squares fitting...?
>
>double x_init[3] = { 1.0, 0.0, 0.0 };
>gsl_vector_view x = gsl_vector_view_array (x_init, p);
>T = gsl_multifit_fdfsolver_lmsder;
>s = gsl_multifit_fdfsolver_alloc (T,
