Hi everyone! My question is as follows:
I have several experimental data, X. X is dependent of 4 different independent variables; X=f(A,B,C,D), which are experimental data too. What I want is the expression of the multi-parametric fit; which I have to “guess” with my data. For example, in the end, I could write X like
X=A^3/B+C*exp(D), or X=B*D…that is what I want to know.
How can I fit them? For example, if I had only X and A, maybe the relation would be like X=A^3 (easily to do with cftool). But what I want to get is a multi-parametric fit.
Is that possible to be done? Is there any toolbox that may help me? I thought about a procedure, but it’s pretty biased. For example, to hit the mark we can use dimensional analysis, but it has some limitations. Also, we can do: X=(A^a)*(B^b)*(C^c)*(D^d)
and fitting with experimental data, finding the coefficients a,b,c,d that minimize the error (an iterative process where we can use nlinfit with its least-squares, or Nelder–Mead Method). But, as you see, limitations are huge. What I want to know is if there is a toolbox that links the behave of the variables, trying and iterating with different function s to reach the best expression for X with its four variables.
I think I am asking too much, and maybe there’s no toolbox that does exactly that…but if there’s any m file you know that would help me to get the most out of calculating whit matlab in this situation (as nlinfit does) I would be very pleased.
Any ideas are welcome. Thanks in advance.