Parent Command
>> OPTION
Subcommand

Description
This command performs GaussNewton steps to minimize the objective
function. The GaussNewton algorithm assumes linearity and can be
described as follows:
GaussNewton steps are efficient if the model is linear (only one iteration required to find minimum) or nearlylinear. If the model is highly nonlinear, GaussNewton steps are usually too large, leading to an inefficient or even unsuccessful step. By default, iTOUGH2 uses the LevenbergMarquardt minimization algorithm, which is a modification of the GaussNewton algorithm.
Example
> COMPUTATION
>> OPTION
>>> use GAUSSNEWTON minimization algorithm
<<<
>> STOP
after >>> :1 ITERATION
<<<
<<
See Also