R: Quantitative Support of Decision Making under Uncertainty

# Quantitative Support of Decision Making under Uncertainty

## Documentation for package ‘decisionSupport’ version 1.115

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

decisionSupport-package | Quantitative Support of Decision Making under Uncertainty.
as.data.frame.mcSimulation | Coerce Monte Carlo simulation results to a data frame.
as.estimate | Create a multivariate estimate object.
as.estimate1d | Create a 1-dimensional estimate object.
chance_event | simulate occurrence of random events
compound_figure | Compound figure for decision support
corMat | Return the Correlation Matrix.
corMat.estimate | Get and set attributes of an 'estimate' object.
corMat<- | Replace correlation matrix.
corMat<-.estimate | Get and set attributes of an 'estimate' object.
decisionSupport | Welfare Decision and Value of Information Analysis wrapper function.
discount | Discount time series for Net Present Value (NPV) calculation
empirical_EVPI | Expected value of perfect information (EVPI) for a simple model with the predictor variable sampled from a normal distribution with.
estimate | Create a multivariate estimate object.
estimate1d | Create a 1-dimensional estimate object.
estimate_read_csv | Read an Estimate from CSV - File.
estimate_read_csv_old | Read an Estimate from CSV - File.
estimate_write_csv | Write an Estimate to CSV - File.
eviSimulation | Expected Value of Information (EVI) Simulation.
gompertz_yield | Gompertz function yield prediction for perennials
hist.eviSimulation | Plot Histograms of results of an EVI simulation
hist.mcSimulation | Plot Histogram of results of a Monte Carlo Simulation
hist.welfareDecisionAnalysis | Plot Histogram of results of a Welfare Decision Analysis
individualEvpiSimulation | Individual Expected Value of Perfect Information Simulation
make_CPT | Make Conditional Probability tables using the likelihood method
mcSimulation | Perform a Monte Carlo simulation.
multi_EVPI | 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.
names.estimate | Get and set attributes of an 'estimate' object.
paramtnormci_fit | Fit parameters of truncated normal distribution based on a confidence interval.
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.
plot.EVPI_outputs | 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.
plot.EVPI_res | Expected value of perfect information (EVPI) for a simple model with the predictor variable sampled from a normal distribution with.
plot_cashflow | Cashflow plot for Monte Carlo simulation results
plot_distributions | Probability distribution plots for various types of Monte Carlo simulation results
plot_empirical_EVPI | Expected value of perfect information (EVPI) for a simple model with the predictor variable sampled from a normal distribution with.
plot_evpi | Visualizing the results of Expected Value of Perfect Information (EVPI) analysis for various types of Monte Carlo simulation results
plot_multi_EVPI | 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.
plot_pls | Visualizing Projection to Latent Structures (PLS) regression outputs for various types of Monte Carlo simulation results
plsr.mcSimulation | Partial Least Squares Regression (PLSR) of Monte Carlo simulation results.
print.mcSimulation | Print Basic Results from Monte Carlo Simulation.
print.summary.eviSimulation | Print the Summarized EVI Simulation Results.
print.summary.mcSimulation | Print the summary of a Monte Carlo simulation.
print.summary.welfareDecisionAnalysis | Print the summarized Welfare Decision Analysis results.
random | Quantiles or empirically based generic random number generation.
random.data.frame | Quantiles or empirically based generic random number generation.
random.default | Quantiles or empirically based generic random number generation.
random.estimate | Generate random numbers for an estimate.
random.estimate1d | Generate univariate random numbers defined by a 1-d estimate.
random.vector | Quantiles or empirically based generic random number generation.
random_state | Draw a random state for a categorical variable
rdist90ci_exact | 90%-confidence interval based univariate random number generation (by exact parameter calculation).
rdistq_fit | Quantiles based univariate random number generation (by parameter fitting).
rmvnorm90ci_exact | 90%-confidence interval multivariate normal random number generation.
row.names.estimate | Get and set attributes of an 'estimate' object.
rposnorm90ci | 90%-confidence interval based truncated normal random number generation.
rtnorm90ci | 90%-confidence interval based truncated normal random number generation.
rtnorm_0_1_90ci | 90%-confidence interval based truncated normal random number generation.
sample_CPT | Sample a Conditional Probability Table
sample_simple_CPT | Make Conditional Probability tables using the likelihood method
scenario_mc | Perform a Monte Carlo simulation for predefined scenarios.
sort.summary.eviSimulation | Sort Summarized EVI Simulation Results..
summary.eviSimulation | Summarize EVI Simulation Results
summary.EVPI_outputs | 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.
summary.EVPI_res | Expected value of perfect information (EVPI) for a simple model with the predictor variable sampled from a normal distribution with.
summary.mcSimulation | Summarize results from Monte Carlo simulation.
summary.welfareDecisionAnalysis | Summarize Welfare Decision Analysis results.
summary_empirical_EVPI | Expected value of perfect information (EVPI) for a simple model with the predictor variable sampled from a normal distribution with.
summary_multi_EVPI | 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.
temp_situations | Situation occurrence and resolution
vv | value varier function
welfareDecisionAnalysis | Analysis of the underlying welfare based decision problem.