Quantitative Support of Decision Making under Uncertainty

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Documentation for package ‘decisionSupport’ version 1.113

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

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.