Package index • mcmodule

All functions

add_group_id(): Add Group IDs to Data Frames

add_prefix(): Add Prefix to Node Names

agg_totals(): Aggregate Across Groups

animal_imports: Example Animal Import Data

at_least_one(): Combined Probability of Events (At least one)

check_mctable(): Checks mctable data

combine_modules(): Combine Two Modules

create_mcnodes(): Create Monte Carlo Nodes from Data and Configuration Table

eval_module(): Evaluate a Monte Carlo Model Expression and create an mcmcmodule

get_edge_table(): Generate Edge Table for Network Construction

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 Construction

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 mcmodule object containing Monte Carlo simulation results Animal Imports Risk Assessment

imports_mctable: Example Monte Carlo Input Table for Import Risk Assessment

keys_match(): Match and align keys between two datasets

mc_keys(): Get Monte Carlo Node Keys

mc_match(): Match Monte Carlo Nodes

mc_match_data(): Match Monte Carlo Node with other data frame

mc_network(): Create Interactive Network Visualization

mc_summary(): Compute summary statistics for an mcnode object

mc_summary_keys(): Get mcnode summary keys

mcnode_na_rm(): Replace NA and Infinite Values in mcnode Objects

node_list_summary(): Include summary and keys in node_list

prevalence_region: Regional Prevalence Data

reset_data_keys(): Reset Data Keys

reset_mctable(): Resets the 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

trial_totals(): Trial Probability and Expected Counts

visNetwork_edges(): Generate visNetwork Edge Table

visNetwork_nodes(): Generate Network Node Table for Visualization

wif_match(): Match Datasets With Differing Scenarios