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", .


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


0.2.1 by Silvana M. Pesenti, a month ago,,

Report a bug at

Browse source code at

Authors: Silvana M. Pesenti [aut, cre] , Alberto Bettini [aut] , Pietro Millossovich [aut] , Andreas Tsanakas [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports Rdpack, Hmisc, nleqslv, reshape2, plyr, ggplot2, stats

Suggests testthat, mvtnorm, spelling, Weighted.Desc.Stat, knitr, rmarkdown, bookdown, ggpubr

See at CRAN