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/> and Pesenti S.M. (2021) "Reverse Sensitivity Analysis for Risk Modelling" <https://www.ssrn.com/abstract=3878879>.
Version: 1.0.0 Depends: R (≥ 3.5.0) Imports: Rdpack (≥ 0.7), Hmisc, nleqslv, reshape2, plyr, ggplot2, stats Suggests: testthat, mvtnorm, spelling, Weighted.Desc.Stat, knitr, rmarkdown, bookdown, ggpubr Published: 2022-01-09 DOI: 10.32614/CRAN.package.SWIM Author: Silvana M. Pesenti [aut, cre], Alberto Bettini [aut], Pietro Millossovich [aut], Andreas Tsanakas [aut], Zhuomin Mao [ctb], Kent Wu [ctb] Maintainer: Silvana M. Pesenti <swimpackage at gmail.com> BugReports: https://github.com/spesenti/SWIM/issues License: GPL-3 URL: https://github.com/spesenti/SWIM, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3515274, https://utstat.toronto.edu/pesenti/?page_id=138 NeedsCompilation: no Language: en-US Citation: SWIM citation info Materials: README NEWS CRAN checks: SWIM results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=SWIM to link to this page.
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