Simplified version of sicr
sicr_single.RdThis function offers a simplified version of sicr(). It can be used to used to
get the gross results for certain development years and reserve classes without building
all the for sicr() required objects in advance.
Usage
sicr_single(
dev_year,
reserve_class,
last_orig_year,
pools,
indices,
age_shift = NULL,
mortality = NULL,
n = 100
)Arguments
- dev_year
Integer or integer vector. Must be greater or equal to 1.
- reserve_class
Integer or integer vector. Must be greater or equal to 0.
- last_orig_year
Last origin year.
- pools
List as output of
generate_pools().- indices
Dataframe for indexation, see details of
prepare_data().- age_shift
Dataframe, see description of age_shift_xmpl. Default: NULL
Only necessary if annuities shall be considered.- mortality
Dataframe, see description of mortality_xmpl. Default: NULL
Only necessary if annuities shall be considered.- n
Number of simulations. Default: 100
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)
sicr_single(dev_year = 1:5,
reserve_class = 0:3,
last_orig_year = 2023,
pools = pools,
indices = indices_xmpl,
age_shift = age_shift_xmpl,
mortality = mortality_xmpl)
#> Reserve_class Dev_year Best_estimate
#> 1 0 5 496.4824
#> 2 0 4 29159.6982
#> 3 0 3 59002.6499
#> 4 0 2 26128.6079
#> 5 0 1 45161.6761
#> 6 1 5 115173.1039
#> 7 1 4 211239.8127
#> 8 1 3 319001.4628
#> 9 1 2 240684.4558
#> 10 1 1 288998.5410
#> 11 2 5 315293.1161
#> 12 2 4 273100.3709
#> 13 2 3 307705.3320
#> 14 2 2 332000.4126
#> 15 2 1 362691.5158
#> 16 3 5 337262.7987
#> 17 3 4 447972.9113
#> 18 3 3 394670.7270
#> 19 3 2 433412.2716
#> 20 3 1 482260.3085