Package: SWIM
Title: Scenario Weights for Importance Measurement
Version: 1.0.0
Authors@R: c(
  person("Silvana M.", "Pesenti", email = "swimpackage@gmail.com", 
  role = c("aut", "cre"), comment = c(ORCID = "0000-0002-6661-6970")), 
  person("Alberto", "Bettini", 
  role = c("aut")), 
  person("Pietro", "Millossovich", 
  role = c("aut"), comment = c(ORCID = "0000-0001-8269-7507")), 
  person("Andreas", "Tsanakas", 
  role = c("aut"), comment = c(ORCID = "0000-0003-4552-5532")),
  person("Zhuomin", "Mao", 
  role = c("ctb")),
  person("Kent", "Wu", 
  role = c("ctb"))
  )
Maintainer: Silvana M. Pesenti <swimpackage@gmail.com>
Description: 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>.
Depends: R (>= 3.5.0)
Imports: Rdpack (>= 0.7), Hmisc, nleqslv, reshape2, plyr, ggplot2,
        stats
RdMacros: Rdpack
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
BugReports: https://github.com/spesenti/SWIM/issues
Encoding: UTF-8
LazyLoad: true
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.1.2
Suggests: testthat, mvtnorm, spelling, Weighted.Desc.Stat, knitr,
        rmarkdown, bookdown, ggpubr
Language: en-US
NeedsCompilation: no
Packaged: 2022-01-09 14:39:55 UTC; silva
Author: Silvana M. Pesenti [aut, cre] (<https://orcid.org/0000-0002-6661-6970>),
  Alberto Bettini [aut],
  Pietro Millossovich [aut] (<https://orcid.org/0000-0001-8269-7507>),
  Andreas Tsanakas [aut] (<https://orcid.org/0000-0003-4552-5532>),
  Zhuomin Mao [ctb],
  Kent Wu [ctb]
Repository: CRAN
Date/Publication: 2022-01-09 15:02:42 UTC
Built: R 4.6.0; ; 2025-12-07 04:51:36 UTC; windows
