Hi,
You are asking a question which in general has no answer. There are an
infinite number of models which can fit your data. You need to find some
possible candidate model forms based on physical properties and then try
fitting to them. You are probably looking for a fit which leaves residues
which are Gaussian and mean zero (but that's not always true...).
Try giving us a clue about where the data come from. Maybe somebody has the
physical background to suggest some models. If not, try plotting the data and
guessing a model from the shape. To me the shape looks vaguely exponential or
logarithmic, so maybe plotting as log-linear or log-log will give a clue.
HTH,
Mike.
-----Original Message-----
From: users-boun...@lists.scilab.org
[mailto:users-boun...@lists.scilab.org]On Behalf Of Larissa Schultze
Sent: 01 July 2013 09:43
To: International users mailing list for Scilab.
Subject: Re: [Scilab-users] Convert x, y, z data into a z=f(x,y) function
Hello all,
first of all, thanks a lot for your effort. I must say that I don't really
have anyone to run to for asking about mathematical models - I could go to the
mathematicians at the University, but I don't know anyone there and I barelly
know where the institute is located...
therefore I decided to insert my simplest table in here (it is actually very
simple) - may be someone here knows which kind of mathematical model I could
use?
I have been searching for it in literature, but I don't seem to be in the
right path...
So attached you will find my data table as well as the scilab commands I used
to create the respective graph. I mean, my data is already
interpolated...shouldn't it be easy to get a function (z,x,y) out of it?
I would be very very thankful for any help...I'm getting a bit desperate...
best regards,
Larissa
Gesendet: Dienstag, 25. Juni 2013 um 11:09 Uhr
Von: "CRETE Denis" <denis.cr...@thalesgroup.com>
An: "International users mailing list for Scilab." <users@lists.scilab.org>
Betreff: Re: [Scilab-users] Convert x, y, z data into a z=f(x,y) function
Hello,
The general procedure for fitting data in the case of 2 variables is the
following:
// First define your mathematical model by changing the following line
deff('z=MyFunction(x,y)', 'z=p(1)*x + p(2)*y + p(3)*x.*y');
// Store all experimental data in a single array ExD; X, Y, Z assumed to be 1
x NZ vectors
ExD=[X;Y;Z];
// Define the error function (to be minimized with respect to the parameters
p)
deff('erro=G(p,ExD)','x=ExD(1),y=ExD(2), z=ExD(3), erro=z-MyFunction(x,y)')
// Fit experimental data contained in W
// The column vector p0 is an initial guess of the values for the parameters
of your Model
[p,err]=datafit(G,ExD,p0)
// you can check values generated with
MyFunction(X,Y)
HTH
Denis
-----Message d'origine-----
De : users-boun...@lists.scilab.org [mailto:users-boun...@lists.scilab.org]
De la part de Dang, Christophe
Envoyé : mardi 25 juin 2013 10:20
À : International users mailing list for Scilab.
Objet : Re: [Scilab-users] Convert x, y, z data into a z=f(x,y) function
Hello,
De la part de Larissa
Envoyé : mardi 25 juin 2013 09:52
> I conducted an experiment and thus my results are composed of x,y,z
> data,
[...]
> but I can't figure out how to get an equation "z=f(x,y)" out of it.
This is more a math problem than a Scilab problem.
You must have a mathematical model, i.e. a parametric formula, then you can
adjust the parameters by regression (or maximum likehood).
You may have theoretical models that derive from elementary assumptions
-- you usually find such model in the bibliography --, or use a "nice model
that fit the global shape"
-- you may ask the math laboratory in your neighbourhood, this is usually
polynomials, exponentials, statistical laws...
So if you come to us with a parametric model, we will be able to help you.
best regards.
--
Christophe Dang Ngoc Chan
Mechanical calculation engineer
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