Given a dataframe of raw results from run_simulations, create summary statistics for the scenario. This is generally the most granular level of useful data for reporting and analysis (full simulation results are rarely directly helpful).

summarize_scenario(simulation_result)

summarize_scenarios(simulation_results)

Arguments

simulation_result

Results object for a single scenario.

simulation_results

Simulation results dataframe.

Value

Dataframe of summary statistics.

Details

Summary stats created include: * Mean/Min/Max/Median are calculated for loss events * Median/Max/VaR are calculated for annual loss expected (ALE) * Mean/Median/Max/Min are calculated for single loss expected (SLE) * Mean percentage of threat capability exceeding difficulty on successful threat events * Mean percentage of difficulty exceeding threat capability on defended events * Vulnerability percentage

Examples

data(mc_simulation_results) # summarize a single scenario summarize_scenario(mc_simulation_results[[1, "results"]])
#> # A tibble: 1 x 14 #> loss_events_mean loss_events_med… loss_events_min loss_events_max ale_median #> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 7.48 7 0 19 682568. #> # … with 9 more variables: ale_max <dbl>, ale_var <dbl>, sle_mean <dbl>, #> # sle_median <dbl>, sle_min <dbl>, sle_max <dbl>, mean_tc_exceedance <dbl>, #> # mean_diff_exceedance <dbl>, mean_vuln <dbl>
# summarize all scenarios in a data frame data(mc_simulation_results) summarize_scenarios(mc_simulation_results)
#> # A tibble: 56 x 18 #> scenario_id domain_id control_descrip… results loss_events_mean #> <chr> <chr> <list> <list> <dbl> #> 1 RS-01 ORG <list [7]> <tibbl… 7.48 #> 2 RS-02 ORG <list [7]> <tibbl… 7.48 #> 3 RS-03 ORG <list [7]> <tibbl… 1.72 #> 4 RS-04 ORG <list [8]> <tibbl… 2.73 #> 5 RS-05 ORG <list [5]> <tibbl… 4.21 #> 6 RS-06 POL <list [4]> <tibbl… 0 #> 7 RS-07 POL <list [4]> <tibbl… 0 #> 8 RS-08 POL <list [4]> <tibbl… 0.042 #> 9 RS-09 COMP <list [2]> <tibbl… 0 #> 10 RS-10 COMP <list [2]> <tibbl… 1.90 #> # … with 46 more rows, and 13 more variables: loss_events_median <dbl>, #> # loss_events_min <dbl>, loss_events_max <dbl>, ale_median <dbl>, #> # ale_max <dbl>, ale_var <dbl>, sle_mean <dbl>, sle_median <dbl>, #> # sle_min <dbl>, sle_max <dbl>, mean_tc_exceedance <dbl>, #> # mean_diff_exceedance <dbl>, mean_vuln <dbl>