3D - Surface Response Plot - Surface of best fit

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Muhammad Hamza Saloojee
Muhammad Hamza Saloojee le 30 Oct 2020
Commenté : Ameer Hamza le 31 Oct 2020
I'm having trouble plotting a curve/surface of best fit through data points. I have z - matrix of 9 data points, which correspend to different combinations of values from an x-vector of 3 and a y-vector of 3. I have managed to plot a surface plot which uses interpolation and fits a curve through the data. Instead of this, I would like to plot a curve of best fit through the data points using a low order polynomial instead.
Assistance would be greatly appreciated.
This is a plot of what I have so far.

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Ameer Hamza
Ameer Hamza le 30 Oct 2020
Modifié(e) : Ameer Hamza le 30 Oct 2020
If you have a curve fitting toolbox, you can use fit(): https://www.mathworks.com/help/curvefit/fit.html function with fitype chosen from polyij as given here: https://www.mathworks.com/help/curvefit/list-of-library-models-for-curve-and-surface-fitting.html#btbcxlm. For example
x; % x-values 9x1
y; % y-values 9x1
z; % z-values 9x1
X = [x y];
Y = z;
fitted_model = fit(X, Y, 'poly22')
If you don't have the toolbox, you can still use mldivide (\) to do least square curve-fitting. For example, suppose you want to fit following model
Then you can do something like this
X = [ones(size(x)) x y x.^2 y.^2 x.*y];
Y = z;
a = X\Y;
  11 commentaires
Muhammad Hamza Saloojee
Muhammad Hamza Saloojee le 30 Oct 2020
This is perfect.
Thank you so much for the assistance!
Much appreciated.
Ameer Hamza
Ameer Hamza le 31 Oct 2020
I am glad to be of help!

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