separateProvision: Claims reserving using separation methods of Taylor.

In acanadis/provision: Statistical Models for Claim Reserving

Description

Claims reserving using separation methods of Taylor.

Usage

separateProvision(lossData, freqData,
modelSep = "arithmetic", lambdaK = 0,
B = 1000, seed = NULL)

Arguments

lossData	Matrix of incremental losses cij, for i = 1,...,k origin years (rows) and for j = 1,...,k development years (columns); filled with NAs for i + j > k.
freqData	Vector with the claims number by origin year i for i = 1,...k.
modelSep	Model to be used, can be arithmetic or geometric. Defaults to "arithmetic".
lambdaK	Percentage of the trend in the inflation index. Defaults to 0.
B	Number of iterations to perform in the bootstrapping procedure. Defaults to 1000.
seed	Seed to make bootstrap reproducible.

Value

A list of 5 elements with:

• triangle Input data (lossData).

• glm.triangle Fitted values by glm modeling.

• model glm model.

• glm.triangle.bootstrap Three-dimensional array of lower triangles from bootstrap procedure.

• summary Summary table.

• params List of output parameters.

Examples

data("TaylorData")
separateProvision(lossData = TaylorData$lossData,
                  freqData = TaylorData$freqData)

acanadis/provision documentation built on May 5, 2019, 3:54 p.m.