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Generates plots to compare best estimates with reserves

plot_reserve_vs_be.Rd

This function generates two plots that graphically compare the entry reserves with the calculated best estimates.

Usage

plot_reserve_vs_be(large_claims_list, sim_result)

Arguments

large_claims_list

Dataframe with one row per known large claim generated by generate_claims_list().

sim_result

Numeric array as a result of sicr().

Value

list of two ggplot2 objects, first compares per reserve class, second compares per development year

Examples

# this example uses data provided with this package
extended_claims_data <- prepare_data(claims_data = claims_data_xmpl,
                                     indices = indices_xmpl,
                                     threshold = 400000,
                                     first_orig_year = 1989,
                                     last_orig_year = 2023,
                                     expected_year_of_growing_large = 3,
                                     reserve_classes = c(1, 200001, 400001, 700001, 1400001),
                                     pool_of_annuities = pool_of_annuities_xmpl)

pools <- generate_pools(extended_claims_data = extended_claims_data,
                        reserve_classes = c(1, 200001, 400001, 700001, 1400001),
                        years_for_pools = 2014:2023,
                        start_of_tail = 17,
                        end_of_tail = 50,
                        lower_outlier_limit = -Inf,
                        upper_outlier_limit = Inf,
                        pool_of_annuities = pool_of_annuities_xmpl)

large_claims_list <- generate_claims_list(extended_claims_data = extended_claims_data,
                                          first_orig_year = 1989,
                                          last_orig_year = 2023)

history <- generate_history_per_claim(data = extended_claims_data,
                                      column = "Cl_payment_cal",
                                      first_orig_year = 1989,
                                      last_orig_year = 2023)
# smallest version
sim_result <- sicr(n = 1,
                   large_claims_list = large_claims_list,
                   first_orig_year = 1989,
                   last_orig_year = 2023,
                   pools = pools,
                   indices = indices_xmpl,
                   history = history)
#> 
 1 of 1 (100%) --- remaining time approx. Inf secs           
#>  
#>  Simulation time: 0,40 secs
#>  
#>  Gross Best Estimate: 120.773.908,60   (standard error: -)
#>            ...Known claims 95.848.308,10
#>            ...IBNR 24.925.600,50

p <- plot_reserve_vs_be(
         large_claims_list = large_claims_list,
         sim_result = sim_result)