Re: Re: Using NonlinearFit/Regress?
- To: mathgroup at smc.vnet.net
- Subject: [mg33917] Re: [mg33876] Re: [mg33856] Using NonlinearFit/Regress?
- From: "Johannes Ludsteck" <johannes.ludsteck at wiwi.uni-regensburg.de>
- Date: Tue, 23 Apr 2002 07:13:30 -0400 (EDT)
- Organization: Universitaet Regensburg
- Sender: owner-wri-mathgroup at wolfram.com
Dear MathGroupr members,
sorry, the following response contained an error.
Of course, it is not possible add the barrrier
to the fit function in NonlinearFit.
Instead it has to be added to the sum of squared residuals.
But this requires setting up a NonlinearFit procedure
manually (using FindMinimum) and thus is probably the
last resort one should take.
Best regards,
Johannes Ludsteck
On 21 Apr 2002, at 6:12, Johannes Ludsteck wrote:
> Dear njg,
> before trying anything else, you should check whether
> the model fits your data. If parameters show the false sign,
> this indicates that the model may not be identified or
> simply false. So please consult a introductory statistics
> or econometrics book before posting such questions.
>
> However, if you anyway have to use the resrictions anyway,
> you can do this, for example by applying a barrier constraint,
> for example
> NonlinearFit[x/(1+a (x-1) + a b x (x-1))
> - If[a<=0||b<=0,Infinity,0.0],...]
> However, this will complicate the minimization and you
> have to provide two starting points for every parameter,
> for example {a, {0.3,0.6}},{b,{0.3,0.6}}.
>
> There are more sophistic methods to apply restrictions. You will
> find them in intermediate or advanced statistics or econometrics
> books.
>
> Best regards,
> Johannes
>
> On 20 Apr 2002, at 2:49, redrooz at yahoo.com wrote:
>
> > I am trying to estimate the parameters {a,b} in the
> > function: x / (1 + a (x-1) + a b x (x-1)) using
> > NonlinearFit[...].
> >
> > The model is known to be a CONCAVE function with
> > 0 < a,b < 1 and b < a. NonlinearFit/Regress
> > always produces negative parameters (a discontinuous
> > function); even if I try to condition them to be
> > positive e.g., {a, 0, 1} and {b, 0, 1}.
> >
> > Any suggestions about using NonlinearFit[...] with the
> > above function?
> >
> > --njg
> >
>
>
>
> <><><><><><><><><><><><>
> Johannes Ludsteck
> Economics Department
> University of Regensburg
> Universitaetsstrasse 31
> 93053 Regensburg
> Phone +49/0941/943-2741
>
<><><><><><><><><><><><><><><><><><>
Johannes Ludsteck
Institut fuer Volkswirtschaftslehre
Lehrstuhl Prof. Dr. Moeller
Universitaet Regensburg
Universitaetsstrasse 31
93053 Regensburg
Tel +49/0941/943-2741