decisionSupport: Quantitative Support of Decision Making under Uncertainty

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 and Clustered Expected Value of Perfect Information. The probabilistic calculations are done via Monte Carlo simulations. This Monte Carlo functionality can be used on its own.

Version: 1.101.1
Depends: R (≥ 3.1.3)
Imports: msm (≥ 1.5), mvtnorm (≥ 1.0.2), stats (≥ 3.1.3)
Suggests: chillR (≥ 0.54), eha (≥ 2.4.2), mc2d (≥ 0.1.15), nleqslv (≥ 2.6), pls (≥ 2.4.3), rriskDistributions (≥ 2.0), testthat (≥ 0.9.1), knitr
Published: 2015-05-20
Author: Lutz Göhring [cre, aut] (ICRAF and Lutz Göhring Consulting), Eike Luedeling [aut] (ICRAF)
Maintainer: Lutz Göhring <lutz.goehring at gmx.de>
License: GPL-3
Copyright: World Agroforestry Centre (ICRAF) 2015
URL: http://www.worldagroforestry.org/
NeedsCompilation: no
CRAN checks: decisionSupport results

Downloads:

Reference manual: decisionSupport.pdf
Package source: decisionSupport_1.101.1.tar.gz
Windows binaries: r-devel: decisionSupport_1.101.1.zip, r-release: decisionSupport_1.101.1.zip, r-oldrel: decisionSupport_1.101.1.zip
OS X Snow Leopard binaries: r-release: decisionSupport_1.101.1.tgz, r-oldrel: decisionSupport_1.101.1.tgz
OS X Mavericks binaries: r-release: decisionSupport_1.101.1.tgz