Manual Page for Command >>> SENSITIVITY
This command makes iTOUGH2 evaluate the sensitivity matrix without performing any optimization.
By default, the scaled Jacobian matrix, i.e., the sensitivity coefficients scaled by the standard deviation
of the observation and expected parameter variation, respectively, is printed to the iTOUGH2 output file:
In addition, the unscaled sensitivity coefficients can be printed by invoking subcommand >>> SENSITIVITY
in block >> OUTPUT. This information can be used to identify the parameters that most strongly affect the system
behavior at actual or potential observation points. Similarly, the relative information content
of actual or potential observations, i.e., the contribution of each data point to the solution of
the inverse problem can be evaluated.
Based on this command, iTOUGH2 also calculates the covariance matrix of the estimated parameters, i.e., the
estimation uncertainty under the assumption that the variances of the residuals are accurately
depicted by the prior covariance matrix Czz. This information along with the global
sensitivity measures (sums of absolute sensitivity coefficients) can be used to optimize the design of an experiment.
It is recommended to use a relatively large perturbation factor (see command >>> PERTURB),
possibly in combination with centered finite difference quotients (see command >>> CENTERED)
for the purpose of sensitivity analysis.
>>> perform a SENSITIVITY analysis for test DESIGN
>>> CENTERED |
>>> PERTURB |
>>> SENSITIVITY MORRIS
>>> SENSITIVITY SALTELLI |
>>> SENSITIVITY (ou)
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Page updated: July 29, 1997