Title: Causal Effect Estimation and Diagnostics with Support Vector
Description: Causal effect estimation in observational data often requires identifying a set of untreated observations that are comparable to some treated group of interest.  This package provides a suite of functions for identifying such a set of observations and for implementing standard and new diagnostics tools.  The primary function, svmmatch(), uses support vector machines to identify a region of common support between treatment and control groups.  A sensitivity analysis, balance checking, and assessment of the region of overlap between treated and control groups is included.  The Bayesian implementation allows for recovery of uncertainty estimates for the treatment effect and all other parameters.

Description: Determines networks of significant synchronization between the discrete states of nodes; see Tumminello et al <doi:10.1371/journal.pone.0017994>.

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

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

Title: Scenario Weights for Importance Measurement
person("Silvana M.", "Pesenti", email = "swimpackage@gmail.com",
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",
Imports: Rdpack (>= 0.7), Hmisc, nleqslv, reshape2, plyr, ggplot2,
Suggests: testthat, mvtnorm, spelling, Weighted.Desc.Stat