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decisionSupport

The R-package decisionSupport is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

The R-package decisionSupport is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with the R-package decisionSupport. If not, see http://www.gnu.org/licenses/.

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CRAN Version

Installation

Install the released version of decisionSupport from CRAN with install.packages("decisionSupport").

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Install

install.packages('decisionSupport')

Monthly Downloads

466

Version

1.114

License

GPL-3

Maintainer

Last Published

April 8th, 2024

Functions in decisionSupport (1.114)

hist.eviSimulation

Plot Histograms of results of an EVI simulation

hist.mcSimulation

Plot Histogram of results of a Monte Carlo Simulation

Gompertz function yield prediction for perennials

individualEvpiSimulation

Individual Expected Value of Perfect Information Simulation

hist.welfareDecisionAnalysis

Plot Histogram of results of a Welfare Decision Analysis

Expected Value of Information (EVI) Simulation.

estimate_read_csv

Read an Estimate from CSV - File.

Create a 1-dimensional estimate object.

estimate_write_csv

Write an Estimate to CSV - File.

Make Conditional Probability tables using the likelihood method

paramtnormci_numeric

Return parameters of truncated normal distribution based on a confidence interval.

plainNames2data.frameNames

Transform model function variable names: plain to data.frame names.

plsr.mcSimulation

Partial Least Squares Regression (PLSR) of Monte Carlo simulation results.

plot_distributions

Probability distribution plots for various types of Monte Carlo simulation results

paramtnormci_fit

Fit parameters of truncated normal distribution based on a confidence interval.

Perform a Monte Carlo simulation.

Visualizing Projection to Latent Structures (PLS) regression outputs for various types of Monte Carlo simulation results

Cashflow plot for Monte Carlo simulation results

Expected value of perfect information (EVPI) for multiple variables. This is a wrapper for the empirical_EVPI function. See the documentation of the empirical_EVPI function for more details.

rdist90ci_exact

90%-confidence interval based univariate random number generation (by exact parameter calculation).

print.summary.mcSimulation

Print the summary of a Monte Carlo simulation.

Visualizing the results of Expected Value of Perfect Information (EVPI) analysis for various types of Monte Carlo simulation results

Quantiles or empirically based generic random number generation.

Quantiles based univariate random number generation (by parameter fitting).

print.mcSimulation

Print Basic Results from Monte Carlo Simulation.

random.estimate1d

Generate univariate random numbers defined by a 1-d estimate.

Draw a random state for a categorical variable

summary.mcSimulation

Summarize results from Monte Carlo simulation.

random.estimate

Generate random numbers for an estimate.

sort.summary.eviSimulation

Sort Summarized EVI Simulation Results..

summary.eviSimulation

Summarize EVI Simulation Results

90%-confidence interval based truncated normal random number generation.

Sample a Conditional Probability Table

summary.welfareDecisionAnalysis

Summarize Welfare Decision Analysis results.

row.names.estimate

Get and set attributes of an estimate object.

temp_situations

Situation occurrence and resolution

value varier function

print.summary.eviSimulation

Print the Summarized EVI Simulation Results.

rmvnorm90ci_exact

90%-confidence interval multivariate normal random number generation.

welfareDecisionAnalysis

Analysis of the underlying welfare based decision problem.

sample_simple_CPT

Make Conditional Probability tables using the likelihood method

print.summary.welfareDecisionAnalysis

Print the summarized Welfare Decision Analysis results.

Perform a Monte Carlo simulation for predefined scenarios.

compound_figure

Compound figure for decision support

Replace correlation matrix.

Create a multivariate estimate object.

Return the Correlation Matrix.

decisionSupport

Welfare Decision and Value of Information Analysis wrapper function.

as.data.frame.mcSimulation

Coerce Monte Carlo simulation results to a data frame.

decisionSupport-package

Quantitative Support of Decision Making under Uncertainty.

simulate occurrence of random events

Expected value of perfect information (EVPI) for a simple model with the predictor variable sampled from a normal distribution with.

Discount time series for Net Present Value (NPV) calculation