fit surface with 4 depended variables

27 Views Asked by At

I would like to be able to represent my measurement results thought a mathematical form.

Unfortunately it seems that the variables are depending and i do not know the relation between them.

What I do have are measurement data from the different four variables at different values.

Once i fix the value of 3 variables, i get a linear behavior

linear Beauvoir.

Once I change the value of the 3 fixed variables and set other values, the linear behavior changes it properties (I get different values for 'a' and 'b').

Is there a way to fit a polynomial for such a non-linear behaviour?

1

There are 1 best solutions below

0
On

Let us suppose that the model is linear with respect to all variables $x,y,w,z$. So, you can write $$F=a_0+a_1x+a_2y+a_3w+a_4z+a_5 xy+a_6xw+a_7xz+a_8yw+a_9yz+a_{10}wz+a_{11}xyw+a_{12}xyz+a_{13}ywz$$ So, you face a multilinear regression problem which is simple if you use matrix formulation.

This is jsut the generalization of $$F=a(y)+b(y) x \qquad \text{with}\qquad a(y)=c+dy \qquad \text{and}\qquad b(y)=e+fy$$ Replacing, you get $$F=c+e x+d y+f x y$$