A multi-OS implementation of the TAMU SWAT model.
The Soil and Water Assessment Tool is a river basin or
watershed scale model developed by Dr. Jeff Arnold for the
USDA-ARS.

Fuka, DR, Walter, MT, Steenhuis, TS, and Easton, ZM

Scenario Weights for Importance Measurement
c(
person("Silvana M.", "Pesenti", email = "swimpackage@gmail.com",
role = c("aut", "cre")),
person("Alberto", "Bettini",
role = c("aut")),
person("Pietro", "Millossovich",
role = c("aut")),
person("Andreas", "Tsanakas",
role = c("aut"))
)
Silvana M. Pesenti [aut, cre],
Alberto Bettini [aut],
Pietro Millossovich [aut],
Andreas Tsanakas [aut]
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",
<doi:10.1016/j.ejor.2018.10.003>.
Rdpack (>= 0.7), Hmisc, nleqslv, reshape2, plyr, ggplot2,
spatstat, stats

Rdpack (>= 0.7), Hmisc, nleqslv, reshape2, plyr, ggplot2,
stats

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