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 > >