Re: Fitting problem
- To: mathgroup at smc.vnet.net
- Subject: [mg95536] Re: Fitting problem
- From: dh <dh at metrohm.com>
- Date: Wed, 21 Jan 2009 06:44:32 -0500 (EST)
- References: <gl4a9k$gk9$1@smc.vnet.net>
Hi,
here is an attempt to tackle your problem:
We have one independent variable, time: t.
we have datasets
d1:{{t1,d11},{t2,d12}..
d2:{{t1,d21},{t2,d22}..
..
we have models with parameters p (not all models may need all parameters):
mod1[t,p1,p2..]
mod22[t,p1,p2..]
...
we define data interpolation functions that we will use to define an
error function:
int1:=Interpolation[d1]
int2:=Interpolation[d2]
...
define an error function:
err[t_,p1_,..]:= (f1[t]-mod1[t,p1,..])^2 + (f2[t]-mod2[t,p1,..])^2+...
we define artificial zero data:
artdat={{t1,0}{t2,0},..}
Finally we fit err against the zero data:
FindFit[artdat,err[t,p1,..],{p1,p2,..},t]
hope this helps, Daniel
Ktota wrote:
> Dear All ;),
>
> i have the following situation:
>
> 5 mathematical models describing the formation of different species.
> The models (so the species) are interdependent, means.. they all have
> the same parameters but some of the have also other additional
> parameter. Example: Model 1 has a parameter "lifetime1"... model 2
> will include this parameter "liftime1" and a new parameter
> "lifetime2".
>
> My trouble is now to find best fit values for the parameters in all
> the models at the same time. I don't want to find a best fit for model
> 1 and then find out when doing best fit for model 2 that model 2 won't
> work with the parameter values found in the first run with model 1. So
> the fitting must consider all the models to find best fit values for
> the parameter.
>
> I wonder if this achievable with mathematica or if i would be better
> of with other software
>
> thank you for your help
>
> Ktota
>
>