Pre-process Run-Off Triangles — AggregateDataPP • clmplus

Pre-process Run-Off Triangles.

Usage

AggregateDataPP(
  cumulative.payments.triangle,
  entries.weights = NULL,
  eta = 1/2
)

Arguments

cumulative.payments.triangle: triangle matrix or matrix array object, input triangle of cumulative payments.
entries.weights: triangle matrix or matrix array model entries weights.
eta: numeric, individual claims exposure in the cell, also known as lost exposure. It must be in the interval (0,1].

Value

An object of class AggregateDataPP. Lists the following elements:

cumulative.payments.triangle: triangle matrix object, input triangle of cumulative payments.
occurrance: matrix array object, the occurrence derived from the input triangle.
exposure: matrix array object, the exposure derived from the input triangle, under the eta claims arrival assumption.
incremental.payments.triangle: triangle matrix object, incremental payments derived from the input.
fit.w: matrix array object, the weights used during estimation.
J: integer, Run-off triangle dimension.
diagonal: numeric, cumulative payments last diagonal.
eta: numeric, Expected time-to-event in the cell. I.e., lost exposure.

References

Pittarello, G., Hiabu, M., & Villegas, A. M. (2023). Replicating and extending chain-ladder via an age-period-cohort structure on the claim development in a run-off triangle. arXiv preprint arXiv:2301.03858.

Examples

data(sifa.mtpl)
sifa.mtpl.rtt <- AggregateDataPP(cumulative.payments.triangle=sifa.mtpl)