nav[aria-label="Primary Navigation"] { padding: 0; & ul { list-style: none; width: 100%; display: flex; flex-direction: row; justify-content: start; align-items: start; gap: 30px; padding: 0; & li { margin: 0; } & ul li { list-style: none; } } }

How to fit model?

unknown

Hi All, Could you please advice how to fit both linear regression and polynomial (degree=3) model together? Thank you.

Accepted answers

I am not sure exactly what you want to do, but it should be quite straightforward.

In the Fit Model platform select Y variable(s), click "Y". Select linear effect and click "Add", select polynomial effect and enter "3" in the "Degree" field and finally select "Polynomial to Degree" in the "Macros" drop-down menu.

All comments

unknown

MS, Thank you for you advice. I would like to explain more what I want to do.
I have 3 input values (x1,x2 and x3) and the output y variable.
As I plot and fit the relations:
(x1,y) = linear regression,
(x2,y) = linear regression,
(x3,y) = polynomial degree=3.
So I would like to get transfer function for prediction the output Y.
I'm not sure which method should I use to get prediction formula by use fit model or neural net. Could you please advice more?
Thank a lot!

Message was edited by: TT

I have only little experience with neural nets, however as you seem to have a clear idea about your model and it's essentially linear I suggest Fit Model platform. Neural Net is more useful if the functional relationships are unknown or highly latent, at least that's my impression.

Anyway, after you set up run your model in Fit Model you can get the prediction formula by choosing Save columns/Prediction Formula under the red triangle in the result window.

unknown

Thanks again MS. I will try as your suggestion.