Combination Functions

combine_capability_parameters()

Combine multiple SME distributions into a single unified view

combine_lognorm()

Weight a set of lognormal parameters into a single distribution

combine_lognorm_trunc()

Weight a set of lognormal parameters into a single distribution

combine_norm()

Weight a set of normal parameters into a single distribution

combine_scenario_parameters()

Combine multiple SME distributions into a single unified view

Create Scenario Objects

prepare_data()

Create one or more quantitative scenarios objects suitable for simulation by 'evaluator'

Distribution Fitting

fit_capabilities()

Fit SME capability estimates to distribution parameters

fit_capabilities_geomean()

Fit capability parameters via a geometric mean

fit_lognorm()

Find parameters that fit quantile values of an unknown lognormal distribution

fit_lognorm_trunc()

Find parameters that fit quantile values of an unknown truncated lognormal distribution

fit_norm_trunc()

Find parameters that fit quantile values of an unknown truncated normal distribution

fit_pois()

Find parameters that fit a poisson distribution.

fit_scenarios()

Fit SME scenario estimates to distribution parameters

fit_scenarios_geomean()

Fit scenario parameters by applying a geometric mean

fit_threat_communities()

Fit each of the threat communities to a distribution

generate_cost_function()

Generate a sum of squares cost function for optimization

Interview Creation

check_readability()

Check the readability of scenario text

make_handouts()

Create a set of interview handouts for a SME

make_scorecard() make_bingo()

Create a scorecard for marking progress through domains in an interview

make_slides()

Create interview slides

Miscellaneous Functions

clean_answers()

Clean extreme answers

collector

collector package

generate_weights()

Generate a weighting table for SMEs based upon their calibration answers

get_smes_domains()

Calculate the prioritized list of domains for a given subject matter expert (SME)

lognormal_to_normal()

Convert lognormal parameters to normal parameters

normal_to_lognormal()

Convert normal parameters to lognormal parameters

Object Classes

enforce_tidyrisk_question_set()

Validate that the parameter passed is a tidyrisk_question_set object

enforce_tidyrisk_response_set()

Validate that the parameter passed is a tidyrisk_response_set object

is_tidyrisk_question_set()

Test if the object is a tidyrisk_question_set

is_tidyrisk_response_set()

Test if the object is a tidyrisk_response_set

tidyrisk_question_set() new_tidyrisk_question_set() as.tidyrisk_question_set() validate_tidyrisk_question_set()

Construct a tidyrisk_question_set object

tidyrisk_response_set() new_tidyrisk_response_set() as.tidyrisk_response_set()

Construct a tidyrisk_response_set object

Provided Data Sets

Reference and sample data sets

mc_calibration_answers

MetroCare Hospital Calibration Answers

mc_capabilities

MetroCare Hospital Capabilities

mc_capability_answers

MetroCare Hospital Capability Answers

mc_capability_parameters_fitted

MetroCare Hospital Capability Parameters (fitted)

mc_domains

MetroCare Hospital Domains

mc_scenario_answers

MetroCare Hospital Scenario Answers

mc_scenario_parameters_fitted

MetroCare Hospital Scenario Parameters (fitted)

mc_scenarios

MetroCare Risk Scenarios

mc_sme_top_domains

MetroCare Hospital SME Top Domains

mc_threat_communities

MetroCare Hospital Threat Communities

mc_threat_parameters_fitted

MetroCare Hospital Threat Parameters (fitted)

calibration_questions

Calibration questions

Read Questions and Responses

Read datasets from disk

read_questions()

Read scenario questions

read_responses()

Read all SMEs responses