R: Modular Monte Carlo Risk Analysis

# Modular Monte Carlo Risk Analysis

## Documentation for package ‘mcmodule’ version 1.3.0

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

## Help Pages

add_prefix | Add Prefix to mcnode Names
agg_totals | Aggregate mcnode Values Across Groups
animal_imports | Example Animal Import Data
at_least_one | Combine Probabilities Assuming Independence
check_mctable | Validate and Prepare mctable Data Frame
combine_modules | Combine Two mcmodule Objects
create_mcnodes | Create mcnodes from Data and Configuration Table
eval_module | Evaluate Monte Carlo Model Expressions
get_edge_table | Generate Edge Table for Network Visualisation
get_mcmodule_nodes | Get Nodes from Monte Carlo Module
get_node_list | Create Node List from Model Expression
get_node_table | Generate Node Table for Network Visualisation
imports_data | Merged Import Data for Risk Assessment
imports_data_keys | Example Data Keys for Animal Imports Risk Assessment
imports_exp | Expression for Calculating Import Infection Probability
imports_mcmodule | Example Monte Carlo Module for Animal Imports Risk Assessment
imports_mctable | Example Monte Carlo Input Table for Import Risk Assessment
keys_match | Match and Align Keys Between Datasets
matrix_to_mcnodes | Create mcnodes from Matrix/Data Frame
mcmodule_converg | Analyse Monte Carlo Simulation Convergence
mcmodule_corr | Calculate Correlation Coefficients Between Inputs and Outputs
mcmodule_dim_check | Check Dimension Compatibility of Monte Carlo Nodes
mcmodule_info | Get Comprehensive Monte Carlo Module Information
mcmodule_tornado | Plot Tornado-Style Correlation Results Across Variates
mcmodule_to_matrices | Convert Monte Carlo Module to Matrices
mcmodule_to_mc | Convert Monte Carlo Module to 'mc2d' Objects
mcnode_na_rm | Replace NA and Infinite Values in mcnode Objects
mcnode_null_rm | Replace NULL mcnode object
mctable_bounds | Extract Morris Bounds From mctable
mctable_sobol_matrices | Sobol sampling matrices from an mctable
mc_compare | Compare Monte Carlo Node Against Baseline Scenario
mc_filter | Filter mcnode Variates by Condition
mc_keys | Extract Key Columns from Monte Carlo Nodes
mc_match | Match Two Monte Carlo Nodes
mc_match_data | Match Monte Carlo Node with Data Frame
mc_network | Create Interactive Network Visualisation
mc_plot | Plot Monte Carlo Node Distribution with Boxplot and Scatter Points
mc_summary | Summarise Monte Carlo Node Values
optim_ndvar | Optimize Number of Variability Iterations Based on Convergence
prevalence_region | Regional Pathogen Prevalence Data
reset_data_keys | Reset Data Keys
reset_mctable | Reset Monte Carlo Inputs Table
reset_sample_design | Reset Global Sample Design
set_data_keys | Set or Get Global Data Keys
set_mctable | Set or Get Monte Carlo Inputs Table
set_sample_design | Set or Get Global Sample Design
test_sensitivity | Test Sensitivity Data for Pathogens
tidy_mcnode | Convert mcnode to Long Format for Plotting
trial_totals | Trial Probability and Expected Counts
visNetwork_edges | Generate Formatted visNetwork Edge Table
visNetwork_nodes | Generate Formatted Network Node Table for Visualisation
which_mcnode | Find mcnodes Matching a Condition
which_mcnode_inf | Find mcnodes with Infinite Values
which_mcnode_na | Find 'mcnode's with Missing Values
wif_match | Match Datasets with Differing Scenarios