- To: mathgroup at smc.vnet.net
- Subject: [mg19665] Re: NonlinearFit
- From: "William M. MacDonald" <wm2 at umail.umd.edu>
- Date: Wed, 8 Sep 1999 02:24:14 -0400
- Organization: University of Maryland
- References: <email@example.com>
- Sender: owner-wri-mathgroup at wolfram.com
In article <7r24q2$6qd at smc.vnet.net> , Virgil Stokes
<virgil.stokes at neuro.ki.se> wrote:
> In reference to Statistics `NonlinearFit` (vers. 1.4, author: John M. Novak)
> for Mathematica Version 3.0.
> I would like to be able to replace the minimization criterion
> that is currently in this package (least-squares). I am trying to
> find a different type of minimization criterion -- one that
> performs better (hopefully) for my particular problem.
> Is it possible to use this package such that one can override the
> current least-squares criterion with a user defined criterion?
> -- Virgil
I thought that all statistical minimized the sum of the squared differences
between data and the modelling function, although different techniques for
doing this exist. So I don't understand your question. But have you tried
Statistics`NonlinearRegression` which uses Levenberg-Marquard and can take
error bars into consideration? It is very sophisticated.
William M. MacDonald
Professor of Physics
University of Maryland
Internet: wm2 at umail.umd.edu
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