An Efficient Code for the Minimization of Highly Nonlinear and Large Residual Least Squares Functions

A new code for solving the unconstrained least squares problem is given, in which a Quasi-NEWTON approximation to the second order term of the Hessian is added to the first order term of the Gauss-Newton method and a lineseareh based upon a quartic model is used. The new algorithm is shown numerically to be more efficient on large residual problems than the Gauss-Newton method and a general purpose minimization algorithm based upon BFGS formula. The listing and the user’s guide of the code is also given