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 | |

summary.EVPI_res | |

summary.mcSimulation | Summarize results from Monte Carlo simulation. |

summary.welfareDecisionAnalysis | Summarize Welfare Decision Analysis results. |

summary_empirical_EVPI | |

summary_multi_EVPI | |

temp_situations | Situation occurrence and resolution |

vv | value varier function |

welfareDecisionAnalysis | Analysis of the underlying welfare based decision problem. |