Function reference • collector

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

Reference

Combination Functions

Create Scenario Objects

Distribution Fitting

Interview Creation

Miscellaneous Functions

Object Classes

Provided Data Sets

Read Questions and Responses