2022/06/22 by Hossein Mohammadi, Mohammadi, Hossein, Peter Challenor +3
Decision Sciences · Computer Science · #Probabilistic and Robust Engineering Design #Simulation Techniques and Applications #Advanced Multi-Objective Optimization Algorithms
paper · pdf · doi:10.48550/arxiv.2206.11348
Sensitivity analysis plays an important role in the development of computer models/simulators through identifying the contribution of each (uncertain) input factor to the model output variability. This report investigates different aspects of the variance-based global sensitivity analysis in the context of complex black-box computer codes. The analysis is mainly conducted using two R packages, namely sensobol (Puy et al., 2021) and sensitivity (Iooss et al., 2021). While the package sensitivity is equipped with a rich set of methods to conduct sensitivity analysis, especially in the case of models with dependent inputs, the package sensobol offers a bunch of user-friendly tools for the visualisation purposes. Several illustrative examples are supplied that allow the user to learn both packages easily and benefit from their features.