>>> MARQUARDT: nue
This command sets the Marquardt parameter nue (default: 10.0). During the optimization process, the Levenberg parameter lambda (see command >>> LEVENBERG) will be divided by the Marquardt parameter nue after each successful iteration, and it will be multiplied by nue if the new parameter set leads to an increased value of the objective function, i.e., if an unsuccessful step was proposed. A big value for lambda means that a small step along the gradient direction is performed. A lambda value of zero is equivalent to a Gauss-Newton step. The former is robust but inefficient, the latter has a quadratic convergence rate but may lead to unsuccessful steps. The Marquardt parameter therefore determines how fast the step size and step direction changes from steepest descent to Gauss-Newton and vice versa.
>>> maximum number of ITERATIONS: 10
>>> set initial LEVENBERG parameter to: 0.1 to make a
safe first step
>>> MARQUARDT parameter : 2.0 (slow change to Gauss-Newton steps)