data.loss.TA {apc}

Motor data

Description

Function that organises loss data in apc.data.list format.

The data set is taken from Table 1 of Verrall (1991), who attributes the data to Taylor and Ashe (1983). It includes a run-off triangle: "response" (X) is paid amounts (units not reported).

Data also analysed in various papers, e.g. England and Verrall (1999).

The data set is in "CL"-format.

At present apc.package does not have functions for either forecasting or for exploiting the counts. For this one can with advantage use the DCL.package.

Usage

data.loss.TA

Value

The value is a list in apc.data.list format.

response

vector of paid amounts, X

dose

NULL.

data.format

logical. Equal to "CL.vector.by.row". Data organised in vectors.

age1

numeric. Equal to 1.

per1

NULL. Not needed when data.format="CL"

coh1

numeric. Equal to 1.

unit

numeric. Equal to 1.

per.zero

NULL. Not needed when data.format="CL"

per.max

NULL. Not needed when data.format="CL"

time.adjust

0. Thus age=1 in cohort=1 corresponds to period=1+1-1+0=1.

label

character. "loss TA".

Author(s)

Bent Nielsen <[e-mail]> 8 Sep 2015 (18 Mar 2015)

Source

Tables 1 of Verrall (1991).

References

England, P., Verrall, R.J. (1999) Analytic and bootstrap estimates of prediction errors in claims reserving Insurance: Mathematics and Economics 25, 281-293

Taylor, G.C., Ashe, F.R. (1983) Second moments of estimates of outstanding claims Journal of Econometrics 23, 37-61

Verrall, R.J. (1991) On the estimation of reserves from loglinear models Insurance: Mathematics and Economics 10, 75-80

See Also

General description of apc.data.list format.

Examples

#########################
##	It is convient to construct a data variable

data	<- data.loss.TA()

##	To see the content of the data

data

#########################
#	Fit chain-ladder model

apc.fit.table(data,"poisson.response")

#	The overdispersed poisson model is experimental at the moment,
#	so not documented
apc.fit.table(data,"od.poisson.response")