Community Member

Joined:

Jun 1, 2016

## Fitting of the parameters of non-linear regression

I can fit the data with non-linear function, namely Mechanistic Growth curve from the JMP library. See the example of the fit in the next figure. The fit equation is BA = a(1 - b e-c *PA).

BA represents a parameter within sheet metal forming domain. I also now that this fit depends on the three parameters: P1 - tooling dimension, P2 - tooling dimension, and P3 - plate thickness. Is it possible to couple the parameters of the fit curve (a, b, and c) and (P1, P2, and P3)? I want to have equation in a form of BA = a(P1, P2, P3)(1 - b(P1, P2, P3) exp-c(P1, P2, P3)*PA).

What I've done so far is, I obtained the a, b, and c for every possible combination of P1, P2, and P3. P1, P2, and P3 are not nominal parameters, however I've done full factorial analysis for all available tooling dimensions and thicknesses.

I don't see where I should go further. Is there a way to obtain this kind of equation or during the non-linear fit or after obtainment of parameters?

2 REPLIES

Joined:

Nov 21, 2014

## Re: Fitting of the parameters of non-linear regression

Hi!  Since you know the relationships you could do this by doing a custom model in the nonlinear platform.  Setting up a custom equation is covered in Chapter 7 of the "Specialized Models" book found under Help > Books > Specialized Models.

Best,

M

Joined:

Nov 21, 2014

## Re: Fitting of the parameters of non-linear regression

Just a follow up to my previous comment.

Susan Walsh did a paper on this (link) that goes through the platform in deep detail.