hgprieto

Syntax >>> CAUCHY Parent Command >> OPTION   Subcommand –   Description This command selects an objective function that corresponds to a Cauchy or Lorentzian distribution, i.e., the probability density function of the residuals r reads: This distribution exhibits more extensive tails compared to the normal distribution, and leads therefore to a more robust estimation […]

Syntax >>>> TEMPERATURE: (-)temp0 Parent Command >>> ANNEAL Subcommand – Description This command defines the initial temperature tau0 for Simulated Annealing minimization. The initial temperature is reduced after each iteration k according to the annealing schedule (see command >>>> SCHEDULE). The temperature tau defines the probability P with which an uphill step delta(S) should be

Syntax >>>> STEP: max_step Parent Command >>> ANNEAL Subcommand – Description This command defines an iteration for Simulated Annealing minimization based on the number of successful steps or total number of steps as defined by max_step. After each iteration is completed, the temperature is reduced according to the annealing schedule (see command >>>> SCHEDULE). An

Syntax >>>> SCHEDULE: beta Parent Command >>> ANNEAL   Subcommand –   Description This command defines the annealing schedule for Simulated Annealing minimization. The annealing schedule is a function describing the temperature reduction (and thus the probability of accepting an uphill step, see command >>> ANNEAL). The temperature is updated after a certain number of

Syntax >>>> ITERATION: max_iter Parent Command >>> ANNEAL Subcommand – Description This command limits the maximum number of iterations performed by the Simulated Annealing minimization algorithm. An iteration is completed if: (1) the maximum number of steps mstep on a temperature level is reached (see command >>>> STEP (a)), or (2) the objective function has

Syntax >>> ANNEAL Parent Command >> OPTION   Subcommand >>>> ITERATION >>>> LIST >>>> SCHEDULE >>>> STEP >>>> TEMPERATURE   Description This command invokes Simulated Annealing to minimize the objective function S. The following steps are performed by iTOUGH2, controlled by a number of fourth-level commands: (1) Define the range of possible parameter values using

Syntax >>> ANDREW: c Parent Command >> OPTION   Subcommand – Description This command selects a robust estimator named Andrews. Given this estimator, the objective function to be minimized is the sum of the cosine functions g(y), where y is the weighted residual: where: with: This objective function does not correspond to a standard probability

Syntax >> OPTION Parent Command > COMPUTATION Subcommand >>> ANDREW >>> ANNEAL >>> CAUCHY >>> DIRECT >>> FORWARD >>> GAUSS-NEWTON >>> GRID SEARCH >>> L1-ESTIMATOR >>> LEAST-SQUARE >>> LEVENBERG-MARQUARDT >>> LIST >>> OBJECTIVE >>> PARALLEL >>> PEST >>> PVM >>> QUADRATIC-LINEAR >>> SELECT >>> SEP >>> SENSITIVITY >>> SIMPLEX >>> STEADY-STATE >>> SVD >>> TORNADO

Syntax >>> PERTURB: (-)alpha (%) Parent Command >> JACOBIAN   Subcommand –   Description This command specifies the perturbation factor alpha for numerical computation of the Jacobian matrix. The columns of the Jacobian matrix are calculated by perturbing the corresponding parameter p by a small amount dp, and taking either a forward or centered finite

Syntax >>> FORWARD (: iswitch) Parent Command >> JACOBIAN Subcommand –   Description With this command the elements of Jacobian matrix are calculated by means of a forward finite difference quotient: The evaluation of the Jacobian thus requires n+1 TOUGH2 simulations, where n is the number of parameters. The size of the perturbation dp can