Run an OpenFAIR model with parameters provided for TEF, TC, DIFF, and LM sampling. If there are multiple controls provided for a scenarios, the arithmetic mean (average) is taken across samples for all controls to get the effective control strength for a given simulation.

openfair_tef_tc_diff_lm(scenario, n = 10^4, title = "Untitled",
  verbose = FALSE)

Arguments

scenario

List of TEF, TC, and LM parameters.

n

Number of simulations to run.

title

Optional name of scenario.

verbose

Whether to print progress indicators.

Value

Dataframe of scenario name, threat_event count, loss_event count, mean TC and DIFF exceedance, and ALE samples.

See also

Examples

data(quantitative_scenarios) scenario <- quantitative_scenarios[1, ] openfair_tef_tc_diff_lm(scenario, 10)
#> # A tibble: 10 x 12 #> title simulation threat_events loss_events vuln mean_tc_exceeda… #> <chr> <int> <int> <int> <dbl> <dbl> #> 1 Unti… 1 30 9 0.3 3.78 #> 2 Unti… 2 30 11 0.367 3.48 #> 3 Unti… 3 23 6 0.261 4.16 #> 4 Unti… 4 19 8 0.421 2.48 #> 5 Unti… 5 24 4 0.167 3.07 #> 6 Unti… 6 36 7 0.194 4.20 #> 7 Unti… 7 32 6 0.188 1.90 #> 8 Unti… 8 31 8 0.258 1.52 #> 9 Unti… 9 41 8 0.195 3.86 #> 10 Unti… 10 20 4 0.2 4.00 #> # ... with 6 more variables: mean_diff_exceedance <dbl>, ale <dbl>, #> # sle_max <dbl>, sle_min <dbl>, sle_mean <dbl>, sle_median <dbl>