Robust Sensitivity Analysis
Robust Sensitivity Analysis (RSA) systematically evaluates how much variation in model outputs can be attributed to uncertainty or variation in model inputs, with an explicit focus on conclusions that remain valid across a wide range of plausible input conditions. It goes beyond standard sensitivity analysis by asking not only which inputs matter most, but which findings are truly robust — stable regardless of assumptions made under uncertainty.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2008). Global Sensitivity Analysis: The Primer. Wiley. · ISBN 9780470059975
- Pianosi, F., Beven, K., Freer, J., Hall, J. W., Rougier, J., Stephenson, D. B., & Wagener, T. (2016). Sensitivity analysis of environmental models: A systematic review with practical workflow. Environmental Modelling & Software, 79, 214-232. · DOI 10.1016/j.envsoft.2016.02.008
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