Weighted least squares polynomial fit.



[p,S] = least2(x,y,n,w)


finds the coefficients of a polynomial
p(x) of degree n that fits the data, p(x(i)) ~= y(i),
in a weighted least-squares sense with weights w(i).
The structure S contains additional info.

This routine is based on polyfit.

The regression problem is formulated in matrix format as:

  A'*W*y = A'*W*A*p

where the vector p contains the coefficients to be found. For a 2nd order polynomial, matrix A would be:

A = [x.^2 x.^1 ones(size(x))];

See also

polyfit polyval least2b