I don’t understand your equation. Weighted least squares requires:
WSSCF = sum(w.*(y-f(x)).^2); % Weighted Least Squares Cost Function
where ‘w’ is the vector of weights, and f(x) is actually a function of ‘x’ that maps ‘x’ to ‘y’. (This is schematic only. The actual function f(b,x) is a function of the parameters ‘b’ as well.
There are several linear and nonlinear parameter estimation functions that can do what you want, but the one you use depends on the nature of your data, the toolboxes you have available, and the model you want to use to fit it.
