fit_scenarios: Fit SME scenario estimates to distribution parameters

In collector: Quantified Risk Assessment Data Collection

Description

Given a set of subject matter expert estimates for the 5th and 95th quantiles of impact and frequency of contact for events, calculate the distribution parameters for TEF and LM. Use a truncated lognormal distribution for LM (losses cannot be infinite in size) and for the TEF.

Usage

fit_scenarios(
  responses,
  maximum_impact = Inf,
  maximum_impact_factor = 10,
  maximum_frequency_factor = 10
)

Arguments

responses	A tidyrisk_response_set object.
maximum_impact	The absolute maximum potential impact of any single loss event.
maximum_impact_factor	Maximum impact factor - scaling factor of a SME's 95 percent maximum loss to limit the impact of any single event.
maximum_frequency_factor	Maximum frequency factor - scaling factor at which to limit frequency of events.

Value

A dataframe.

See Also

Other distribution fitting functions: combine_lognorm_trunc(), combine_lognorm(), combine_norm(), fit_capabilities_geomean(), fit_capabilities(), fit_lognorm_trunc(), fit_lognorm(), fit_norm_trunc(), fit_pois(), fit_scenarios_geomean(), fit_threat_communities(), generate_cost_function(), lognormal_to_normal(), normal_to_lognormal()

Examples

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collector documentation built on Feb. 22, 2020, 1:11 a.m.