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multivariable regression, known structure, calculate coefficients

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Ansgar Elles
Ansgar Elles on 8 Aug 2020
Commented: the cyclist on 11 Aug 2020
Hi, I have the equations for calculating the corrosion rate (r_corr) of different materials (e(1) steel, e(2) zinc, e(3) copper, e(4) aluminium, see below). (According to ISO 9223).
My goal is now to create a fifth equation for another type of material. I have generated data where r_corr was measured along P_d, RH (relative humidity), T and S_d.
How can you calculate the coefficients (marked below in yellow) for the new material? I want to use the structure of the equations below. So to speak:
r_corr = a * P_d^b * exp(c * RH + f_St) + d * S_d^e*exp(f * RH + g * T)
Thank you very much!

Answers (1)

the cyclist
the cyclist on 8 Aug 2020
If you have the Statistics and Machine Learning Toolbox, you should be able to use the fitnlm function.
the cyclist
the cyclist on 11 Aug 2020
I'm not too surprised. With 7 free parameters, you'll like need a lot of data to fit a stable statistical model.
If you can post your data, it might help people have some more specific ideas.

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