Based on samples from a Monte Carlo simulation, the first-order sensitivity indices can be estimated without additional model calls. This requires the numerical approximation of a one-dimensional conditional expectation.
In factor prioritization, the input parameters are ranked according to their importance on the model output. The first-order sensitivity indices are a commonly applied sensitivity measure for that purpose.
A first-order sensitivity index quantifies the effect of varying the associated model input parameter alone. The first-order sensitivity indices are well-suited for factor prioritization.
Sensitivity analysis assesses how the input parameters and their uncertainties influence the model output. It is essential to define the goal of the analysis as the first step of any sensitivity analysis.
