3D Least squares polynomial fit in x and y
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Often, measured data is comprised of N sampled values of z, evaluated at N locations (x,y). With this function, you can calculate the coefficients of the best-fit x,y polynomial using a linear least squares approximation.
You can use this function if you have a set of N data triplets x,y,z, and you want to find a polynomial f(x,y) of a specific form (i.e. you know the terms you want to include (e.g. x^2, xy^3, constant, x^-3, etc.) in your fitting polynomial.
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Thomas (2024). 3D Least squares polynomial fit in x and y (https://www.mathworks.com/matlabcentral/fileexchange/24062-3d-least-squares-polynomial-fit-in-x-and-y), MATLAB Central File Exchange. Abgerufen .
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- MATLAB > Mathematics > Elementary Math > Polynomials >
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Version | Veröffentlicht | Versionshinweise | |
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1.0.0.0 |