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decisionSupport
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", "1.114")
Attach the package and use:
library("decisionSupport")
Maintained by
Eike Luedeling
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.decisionSupport . decisionSupport results . decisionSupport.pdf . Applying the mcSimulation function in decisionSupport . decisionSupport_1.114.tar.gz . decisionSupport_1.114.zip . decisionSupport_1.114.zip . decisionSupport_1.114.zip . decisionSupport_1.114.tgz . decisionSupport_1.114.tgz . decisionSupport_1.114.tgz . decisionSupport_1.114.tgz . decisionSupport_1.114.tgz . decisionSupport_1.114.tgz . decisionSupport archive . https://CRAN.R-project.org/package=decisionSupport .
First Published: 2015-05-20
Latest Update: 2023-10-05
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 1.114, https://cran.r-project.org/web/packages/decisionSupport. Accessed 29 Mar. 2025.
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)
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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