Supporting the quantitative analysis of binary welfare based decision making processes using Monte Carlo simulations. Decision support is given on two levels: (i) The actual decision level is to choose between two alternatives under probabilistic uncertainty. This package calculates the optimal decision based on maximizing expected welfare. (ii) The meta decision level is to allocate resources to reduce the uncertainty in the underlying decision problem, i.e to increase the current information to improve the actual decision making process. This problem is dealt with using the Value of Information Analysis. The Expected Value of Information for arbitrary prospective estimates can be calculated as well as Individual Expected Value of Perfect Information. The probabilistic calculations are done via Monte Carlo simulations. This Monte Carlo functionality can be used on its own.

Documentation

Manual: decisionSupport.pdf
Vignette: None available.

Maintainer: Eike Luedeling <eike at eikeluedeling.com>

Author(s): Eike Luedeling* (ICRAF), Lutz Göhring* (ICRAF and Lutz Göhring Consulting)

Install package and any missing dependencies by running this line in your R console:

install.packages("decisionSupport")

Depends R (>= 3.1.3)
Imports msm(>=1.5), mvtnorm(>=1.0.2), stats (>= 3.1.3)
Suggests chillR(>=0.62), eha(>=2.4.2), mc2d(>=0.1.15), nleqslv(>=2.6), pls(>=2.4.3), rriskDistributions(>=2.0), testthat(>=0.9.1), knitr
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Package decisionSupport
Materials
URL http://www.worldagroforestry.org/
Task Views
Version 1.101.2
Published 2016-04-26
License GPL-3
BugReports
SystemRequirements
NeedsCompilation no
Citation
CRAN checks decisionSupport check results
Package source decisionSupport_1.101.2.tar.gz