Given a dataframe of quantitative scenarios, run an OpenFAIR Monte Carlo simulation for each scenario, returning a combined dataframe of all results.

run_simulations(scenario, simulation_count = 10000L,
  model = "openfair_tef_tc_diff_lm", ale_maximum = NULL,
  verbose = FALSE)

Arguments

scenario

Quantitative scenarios.

simulation_count

Number of simulations for each scenario.

model

OpenFAIR model to use.

ale_maximum

Apply a maximum per year, per simulation, loss maximum.

verbose

Whether verbose console output is requested.

Value

Dataframe of raw results.

Examples

data(quantitative_scenarios) # run a single scenario in a trivial number (10) of trials run_simulations(quantitative_scenarios[1, ], 10)
#> # A tibble: 10 x 13 #> domain_id scenario_id simulation threat_events loss_events vuln #> <chr> <chr> <int> <int> <int> <dbl> #> 1 ORG 1 1 30 9 0.3 #> 2 ORG 1 2 30 11 0.367 #> 3 ORG 1 3 23 6 0.261 #> 4 ORG 1 4 19 8 0.421 #> 5 ORG 1 5 24 4 0.167 #> 6 ORG 1 6 36 7 0.194 #> 7 ORG 1 7 32 6 0.188 #> 8 ORG 1 8 31 8 0.258 #> 9 ORG 1 9 41 8 0.195 #> 10 ORG 1 10 20 4 0.2 #> # ... with 7 more variables: mean_tc_exceedance <dbl>, #> # mean_diff_exceedance <dbl>, ale <dbl>, sle_max <dbl>, sle_min <dbl>, #> # sle_mean <dbl>, sle_median <dbl>