3D Least squares polynomial fit in x and y

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.