ChainLadder (version 0.1.2-8)

ChainLadder-package: Various chain-ladder methods for claims reserving

Description

The ChainLadder-package grew out of presentations the author gave at the Stochastic Reserving Seminar at the Institute of Actuaries in November 2007. This package has currently implementations for the Mack-, Munich- and Bootstrap-chain-ladder methods. A presentation given at the R-user conference 2008 in Dortmund is available in the doc folder of the installation directory of the ChainLadder package.

The R command searchpaths()[grep('ChainLadder', searchpaths())] will tell you the exact path to the directory. An example spreadsheet is provided in the Excel folder of the above path and demonstrates how to use the ChainLadder functions in Excel. For the the spreadsheet you will need the RExcel-Addin, see http://sunsite.univie.ac.at/rcom/. To install the Add-in get the R-package RExcelInstaller and call installRExcel(). If you are also interested in loss distributions modeling, risk theory (including ruin theory), simulation of compound hierarchical models and credibility theory check out the actuar package by C. Dutang, V. Goulet and M. Pigeon.

Details

ll{ Package: ChainLadder Type: Package Version: 0.1.2 Date: 2008-10-12 License: GPL version 2 or later }

References

Thomas Mack. Distribution-free calculation of the standard error of chain ladder reserve estimates. Astin Bulletin. Vol. 23. No 2. 1993. pp.213:225

Thomas Mack. The standard error of chain ladder reserve estimates: Recursive calculation and inclusion of a tail factor. Astin Bulletin. Vol. 29. No 2. 1999. pp.361:366

Gerhard Quarg and Thomas Mack. Munich Chain Ladder. Blatter DGVFM 26. Munich. 2004.

England, PD and Verrall, RJ. Stochastic Claims Reserving in General Insurance (with discussion). British Actuarial Journal 8. III. 2002

B. Zehnwirth and G. Barnett. Best Estimates for Reserves. Proceedings of the CAS. Volume LXXXVII. Number 167.November 2000.

Examples

RAA  

MCL=MackChainLadder(RAA)
MCL
plot(MCL)

# BootChainLadder
B <- BootChainLadder(RAA, R=999, process.distr="gamma")
B
plot(B)
# fitdistribution
library(MASS)
# fit a log-normal distribution 
fit <-  fitdistr(B$IBNR.Totals, "lognormal")
fit
plot(ecdf(B$IBNR.Totals))
curve(plnorm(x,fit$estimate["meanlog"], fit$estimate["sdlog"]), col="red", add=TRUE)

 # Munich Chain Ladder
 MCLpaid
 MCLincurred
 
 MCL = MunichChainLadder(MCLpaid, MCLincurred)
 MCL
 plot(MCL)