adlp_partition: Accident and Development period Adjusted Linear Pools...

In ADLP: Accident and Development Period Adjusted Linear Pools for Actuarial Stochastic Reserving

Accident and Development period Adjusted Linear Pools partition function

Description

General framework for any user-defined function for partitions of claims triangle data.

Usage

adlp_partition(df, ...)

adlp_partition_none(df)

adlp_partition_ap(df, tri.size, size = 1, weights = rep(1, size))

Arguments

df	data.frame format of claims and related information for each cell. Dataframe will have columns origin and dev as columns 1 and 2 respectively.
...	Other parameters used to calculate ADLP partitions
tri.size	Triangle size in claims
size	Number of partitions
weights	a vector of weights for the size of each partition.

Details

adlp_partition_none is the default functionality with no partitions. This is equivalent to the standard linear pooling.

adlp_partition_ap will partition the claims triangle by accident period, Where the choice of accident period to partition will be determined to most closely resemble the desired weights.

The choice of accident period relies on a greedy algorithm that aims to find the accident period that provides the amount of cells that is larger or equal to the desired split.

Value

List containing the df as a result of the partitions.

See Also

adlp_partition_none, adlp_partition_ap

Examples

data("test_claims_dataset")
adlp_partition_none(test_claims_dataset)

data("test_claims_dataset")
adlp_partition_ap(test_claims_dataset, tri.size = 40, size = 3)

ADLP documentation built on May 29, 2024, 2:12 a.m.