An efficient sensitivity analysis for stochastic models based on Monte Carlo samples. Provides weights on simulated scenarios from a stochastic model, such that stressed random variables fulfil given probabilistic constraints (e.g. specified values for risk measures), under the new scenario weights. Scenario weights are selected by constrained minimisation of the relative entropy to the baseline model. The 'SWIM' package is based on Pesenti S.M, Millossovich P., Tsanakas A. (2019) "Reverse Sensitivity Testing: What does it take to break the model", <openaccess.city.ac.uk/id/eprint/18896/>.
|Author||Silvana M. Pesenti [aut, cre], Alberto Bettini [aut], Pietro Millossovich [aut], Andreas Tsanakas [aut]|
|Maintainer||Silvana M. Pesenti <email@example.com>|
|URL||https://github.com/spesenti/SWIM https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3515274 https://utstat.toronto.edu/pesenti/?page_id=138|
|Package repository||View on GitHub|
Install the latest version of this package by entering the following in R:
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.