Package index • sicr

All functions

active_annuities_ok(): Checking active_annuities dataframe for possible mistakes

active_annuities_xmpl: Example of an active annuities dataframe

add_classes(): Adding reserve classes to extended_claims_data

add_columns(): Add columns

add_indexed_columns(): Add indexed columns

add_missing_years(): Add missing rows

add_sicr_aggr_worksheet(): Create Excel sheet by adding or subtracting other sheets

add_sicr_worksheet(): Add formatted worksheet to a workbook

add_transition_factor(): adding column Transition_factor to dataframe expanded_indices

age_shift_ok(): Checking age_shift dataframe for possible mistakes

age_shift_xmpl: (unrealistic!) example of an age shift dataframe

aggregate_large_claims_results(): Aggregating data and simulation results to payments and reserves matrices

all_annuities_paid_xmpl: Example matrix with payments for all annuities (e.g. small + large + special claims)

all_annuities_reserved_xmpl: Example matrix with reserves for all annuities (e.g. small + large + special claims)

all_claims_paid_xmpl: Example matrix with payments for all claims (e.g. small + large + special claims)

all_claims_reserved_xmpl: Example matrix with reserves for all claims (e.g. small + large + special claims)

apply_index(): Indexing payments to another year

attach_future_annuities(): Attach future annuities to extended_claims_data

best_estimate2cashflow(): rolling out best estimate vector

cal_year2dev_year(): Transform calendar year triangle to development year triangle

check_column_type(): Check column type

check_dataframe_structure(): Check structure of a dataframe

claims_data_ok(): Checking claims_data dataframe for possible mistakes

claims_data_xmpl: Example of a claims data dataframe

cl_factor(): chain ladder factor

compute_small_claims(): Calculate small claims results in one step

compute_special_claims(): Compute everything belonging to the chosen special claims

convert_single2dev_year_prediction(): Converting a prediction per single claim into a prediction per development year.

convert_single2dev_year_triangle(): Generating triangle per development year from historic cashflow of single claims

cum2inc(): cumulative to incremental claims triangle

cut2history(): Cuts out the history part of a matrix with historic and future payments

cut2prediction(): Cuts out the prediction part of a matrix with historic and predicted payments

dev_year2cal_year(): Transform development year triangle to calendar year triangle

expand_historic_indices(): expand dataframe historic_indices by expected future indices

exposure_ok(): Checking exposure dataframe for possible mistakes

exposure_xmpl: Example of an exposure dataframe

fill_up_triangle(): Filling up claims triangle to rectangle

filter_large_claims(): Filtering extended_claims_data to large claims and add derived columns

generate_annuities_prediction(): Generate annuities prediction per development year from rolled out single annuities

generate_annuity_payments(): Create matrix of agreed future payments (without mortality probabilities)

generate_annuity_probabilities(): Create matrix of future mortality probabilities

generate_claims_list(): Generate claims list

generate_history_per_claim(): Generating claims history from dataframe

generate_ibnr_pools(): Generate ibnr pools

generate_pattern(): Claims Development Pattern

generate_pools(): Generate pools to sample from

generate_small_claims_annuities_parameters(): Estimate for future annuities stemming from small claims

generate_small_claims_future_annuities(): Estimate for future annuities stemming from small claims

generate_triangle(): Generating claims history triangle from dataframe

generate_xl_indices_per_claim(): Helper function to create a matrix with indices per claim stemming from reinsurance treaty clause

get_additive_ibnr_model(): Generating additive model to estimate future ibnr claim numbers

get_expected_ibnr_numbers(): Derive expected future ibnr numbers

historic_indices_ok(): Checking historic_indices dataframe for possible mistakes

historic_indices_xmpl: Example of a historic_indices dataframe

ibnr_transform2dataframe(): Transform exptected ibnr matrix to dataframe

inc2cum(): incremental to cumulative claims triangle

indices_ok(): Checking indices dataframe for possible mistakes

indices_xmpl: Example of a indices dataframe

merge_results(): merge paid and incurred results

minimal_active_annuities_xmpl: Minimal example of an active annuities dataframe

minimal_claims_data_xmpl: Minimal example of a claims data dataframe

minimal_pool_of_annuities_xmpl: Minimal example of a pool of annuities dataframe

mortality_ok(): Checking mortality dataframe for possible mistakes

mortality_xmpl: (unrealistic!) example of a mortality dataframe

nice_format(): Easy to read formatting for numbers

plot_identify_special_claims(): Generates plot to identify special claims

pools2dataframe(): Converts pools into a dataframe

pool_of_annuities_ok(): Checking pool_of_annuities dataframe for possible mistakes

pool_of_annuities_xmpl: Example of a pool of annuities dataframe

prepare_data(): Prepare data for further usage

prepare_ibnr(): Prepares necessary ibnr objects

reduce_data(): Reduce claims data to possible large claims

reinsurance_ok(): Checking reinsurance dataframe for possible mistakes

reinsurance_xmpl: Example of a reinsurance structures dataframe

result2best_estimate(): deriving best estimate

roll_out_active_annuities(): Rolling out active annuities corresponding to large claims

roll_out_annuity(): Rolling out one or more annuities

roll_out_single_claim(): Converting a reserve into a cashflow by given patterns

round_expected_ibnr_numbers(): Rounding expected ibnr matrix

sicr(): Simulation of large claims per stochastic individual claims reserving

skeleton_prediction(): Skeleton for payments prediction

skeleton_triangle(): Skeleton for history triangle

tail_factor(): Payment transition from first tail year to another development year

xl_cashflow(): Calculate reinsurer's payments for xl-treaty