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decisionSupport  

Quantitative Support of Decision Making under Uncertainty
View on CRAN: Click here


Download and install decisionSupport package within the R console
Install from CRAN:
install.packages("decisionSupport")

Install from Github:
library("remotes")
install_github("cran/decisionSupport")

Install by package version:
library("remotes")
install_version("decisionSupport", "1.115")



Attach the package and use:
library("decisionSupport")
Maintained by
Eike Luedeling
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-05-20
Latest Update: 2025-09-03
Description:
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.
How to cite:
Eike Luedeling (2015). decisionSupport: Quantitative Support of Decision Making under Uncertainty. R package version 1.115, https://cran.r-project.org/web/packages/decisionSupport. Accessed 06 Mar. 2026.
Previous versions and publish date:
1.101.1 (2015-05-20 01:20), 1.101.2 (2016-04-26 08:44), 1.102.1 (2017-10-06 14:57), 1.102.2 (2017-11-13 16:17), 1.103.2 (2017-11-27 14:19), 1.103.6 (2017-11-28 01:10), 1.103.7 (2018-05-16 00:33), 1.103.8 (2018-10-15 12:00), 1.105.2 (2019-10-16 22:20), 1.105.3 (2020-05-12 07:00), 1.106 (2021-03-01 18:40), 1.107 (2021-10-16 16:30), 1.108 (2021-10-17 01:20), 1.109 (2021-11-19 08:20), 1.110 (2022-02-18 10:00), 1.111 (2022-05-09 14:30), 1.113 (2023-10-06 01:20), 1.114 (2024-04-08 17:20)
Other packages that cited decisionSupport R package
View decisionSupport citation profile
Other R packages that decisionSupport depends, imports, suggests or enhances
Complete documentation for decisionSupport
Functions, R codes and Examples using the decisionSupport R package
Some associated functions: as.data.frame.mcSimulation . chance_event . compound_figure . corMat-set . corMat . decisionSupport-package . decisionSupport . discount . empirical_EVPI . estimate . estimate1d . estimate_read_csv . estimate_write_csv . eviSimulation . gompertz_yield . hist.eviSimulation . hist.mcSimulation . hist.welfareDecisionAnalysis . individualEvpiSimulation . make_CPT . mcSimulation . multi_EVPI . paramtnormci_fit . paramtnormci_numeric . plainNames2data.frameNames . plot_cashflow . plot_distributions . plot_evpi . plot_pls . plsr.mcSimulation . print.mcSimulation . print.summary.eviSimulation . print.summary.mcSimulation . print.summary.welfareDecisionAnalysis . random.estimate . random.estimate1d . random . random_state . rdist90ci_exact . rdistq_fit . rmvnorm90ci_exact . row.names.estimate . rtnorm90ci . sample_CPT . sample_simple_CPT . scenario_mc . sort.summary.eviSimulation . summary.eviSimulation . summary.mcSimulation . summary.welfareDecisionAnalysis . temp_situations . vv . welfareDecisionAnalysis . 
Some associated R codes: as.data.frame.mcSimulation.R . chance_event.R . compound_figure.R . decisionSupport-package.R . decisionSupport.R . discount.R . empirical_EVPI.R . estimate.R . estimate1d.R . estimate_read_csv_old.R . eviSimulation.R . global_variables.R . gompertz_yield.R . hist.mcSimulation.R . individualEvpiSimulation.R . make_CPT.R . mcSimulation.R . multi_EVPI.R . paramtnormci_fit.R . paramtnormci_numeric.R . plainNames2data.frameNames.R . plot_cashflow.R . plot_distributions.R . plot_evpi.R . plot_pls.R . plsr.mcSimulation.R . print.mcSimuation.R . print.summary.mcSimulation.R . random.R . random_state.R . rdist90ci_exact.R . rdistq_fit.R . rmvnorm90ci_exact.R . rtnorm90ci.R . sample_CPT.R . sample_simple_CPT.R . scenario_mc.R . summary.mcSimulation.R . temp_situations.R . vv.R . welfareDecisionAnalysis.R .  Full decisionSupport package functions and examples
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