data.loss.TA {apc} | R Documentation |
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
.
data.loss.TA
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". |
Bent Nielsen <bent.nielsen@nuffield.ox.ac.uk> 8 Sep 2015 (18 Mar 2015)
Tables 1 of Verrall (1991).
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
General description of apc.data.list
format.
######################### ## 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")