spesenti/SWIM: Scenario Weights for Importance Measurement

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/>.

Getting started

Package details

AuthorSilvana M. Pesenti [aut, cre], Alberto Bettini [aut], Pietro Millossovich [aut], Andreas Tsanakas [aut]
MaintainerSilvana M. Pesenti <swimpackage@gmail.com>
LicenseGPL-3
Version0.2.2
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 repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("spesenti/SWIM")
spesenti/SWIM documentation built on Oct. 1, 2020, 7:07 p.m.