Links and software of interest
Software packages and addons that are useful for performing sensitivity analysis.
💻 The sensitivity package in R.
💻 UQLab, a MATLAB-based uncertainty quantification framework with state-of-the art, highly optimized open source algorithms (and good documentation).
💻 SIML@B provides a set of online tools to perform uncertainty analysis and sensitivity analysis (UASA) of model output.
💻 sensobol, An R Package to Compute Variance-Based Sensitivity Indices.
💻 SALib, Sensitivity Analysis Library in Python. Includes Sobol’, FAST, DGSM, PAWN, moment independent.
The following references give a good guide to sensitivity analysis and related topics.
📖 Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D. Saisana, M., Tarantola, S., 2008, Global Sensitivity Analysis. The Primer, John Wiley & Sons publishers.
📖 S. Da Veiga, F. Gamboa, B. Iooss and C. Prieur. Basics and trends in sensitivity analysis - Theory and practice in R, SIAM, 2021.
📖 Interpretability for Industry 4.0: Statistical and Machine Learning Approaches, A. Lepore, B. Palumbo and J-M. Poggi (Eds), Springer, 2022
🔗 GdR MASCOT-NUM is a French Research Group dealing with stochastic methods for the analysis of numerical codes. Its main objective is to coordinate research efforts in this scientific area, which is often called design, modeling and analysis of computer experiments.
🔗 andreasaltelli.eu is the personal page of veteran sensitivity analysis researcher Andrea Saltelli, and hosts many useful resources (inlcuding books) on sensitivity analysis.