[Scilab-users] Convert x, y, z data into a z=f(x,y) function

[CRETE Denis]

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-bounces at lists.scilab.org [mailto:users-bounces at 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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