**Syntax**

` >>> MARQUARDT: nue`

**Parent Command**

` >> CONVERGE
`

**Subcommand**

` -
`

**Description**

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.

**Example**

` > COMPUTATION
>> CONVERGE
>>> 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)
<<<
<<`

**See Also**

` >>> LEVENBERG
`