The Sensitivity Analysis Toolbox supports “state of the art” sensitivity analysis methods (local as well as global). Sensitivity analysis (SA) is used to assess the influence of model parameters on model predictions.
The Sensitivity toolbox is an optional fully integrated module for Ecolego and is thus most suitable for using with Ecolego models, although external models are also supported by exporting/importing samples of model inputs and/or model predictions.
Correlations between parameters may be induced by rank order correlation (method of Iman and Conover). The supported sampling techniques are: Monte carlo, Latin Hypercube and Quasi-random LpTau. The SA methods included are:
Graphical User Interface (GUI) lets you:
It is also possible to perform sensitivity analysis on groups of parameters (using extensions of the Sobol or EFAST methods). In this way the influence of each of the selected parameters as well as any combination of them is accounted for when computing the sensitivity indices on a given output.