Package index • mcmodule

All functions

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

mcmodule_converg() experimental: Analyse Monte Carlo Simulation Convergence

mcmodule_corr() experimental: Calculate Correlation Coefficients Between Inputs and Outputs

mcmodule_dim_check() experimental: Check Dimension Compatibility of Monte Carlo Nodes

mcmodule_info(): Get Comprehensive Monte Carlo Module Information

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

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() experimental: Create Interactive Network Visualisation

mc_plot() experimental: Plot Monte Carlo Node Distribution with Boxplot and Scatter Points

mc_summary(): Summarise Monte Carlo Node Values

prevalence_region: Regional Pathogen Prevalence Data

reset_data_keys(): Reset Data Keys

reset_mctable(): Reset Monte Carlo Inputs Table

set_data_keys(): Set or Get Global Data Keys

set_mctable(): Set or Get Monte Carlo Inputs Table

test_sensitivity: Test Sensitivity Data for Pathogens

tidy_mcnode() experimental: 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 mcnodes with Missing Values

wif_match(): Match Datasets with Differing Scenarios