# Create a new equation from a model in order to nonlinear, polynomial multiple regression, etc. for multiple many (4 or above) variables

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Hello. There are column vectors of at least 1000 data of 6 different types (variables). These parameters, called "q, E, w, x, σ, KP", represent each column vector and each variable. Using these column vectors, I want to suggest a new equation via nonlinear, polynomial multiple regression, etc. methods for multiple (4 or more) variables. What is the way to create a new equation from a model for? In the MATLAB Curve Fitting toolbox, I saw that a model can be created for, "X, Y, Z" inputs, a maximum of 3 variables. What's the way to can be done that?
My aim: Create an equation: f(q, E, w, x, σ, KP)=y and show this mathematically model like "q*a1+E*a2+w*a3+w*a4+x*a5+σ*a6+KP*a7" or different degree, variation and mathematical approaching.

Abdolkarim Mohammadi on 23 Aug 2020
Your have a linear relationship and the best option for you is the multiple linear regression. See the documentation of the regress() function:
https://www.mathworks.com/help/stats/regress.html

R2020a

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