Stochastic reserving with R: ChainLadder 0.1.5-1 released
Today we published version 0.1.5-1 of theChainLadder
package for R. It provides methods which are typically used in insurance claims reserving to forecast future claims payments.Claims development and chain-ladder forecast of the RAA data set using the Mack method |
Initially the package came with implementations of the Mack-, Munich- and Bootstrap Chain-Ladder methods. Since version 0.1.3-3 it also provides general multivariate chain ladder models by Wayne Zhang. Version 0.1.4-0 introduced new functions on loss development factor fitting and Cape Cod by Daniel Murphy following a paper by David Clark. Version 0.1.5-0 has added loss reserving models within the generalized linear model framework following a paper by England P. and Verrall R. (1999) implemented by Wayne Zhang.
For more details see the project web site: http://code.google.com/p/chainladder/ and an early blog entry about R in the insurance industry.
Changes in version 0.1.5-1:
- Internal changes to
plot.MackChainLadder
to pass new checks introduced by R 2.14.0.
- Commented out unnecessary creation of 'io' matrix in
ClarkCapeCod
function. Allows for analysis of very large matrices forCapeCod
without running out of RAM. 'io' matrix is an integral part ofClarkLDF
, and so remains in that function.
-
plot.clark
method
- Removed "conclusion" stated in
QQplot
of clark methods.
- Restore 'par' settings upon exit
- Slight change to the title
- Removed "conclusion" stated in
- Reduced the minimum 'theta' boundary for weibull growth function
- Added warnings to
as.triangle
if origin or dev. period are not numeric
Here is a little example using the googleVis package to display the RAA claims development triangle:
library(ChainLadder) library(googleVis) data(RAA) # example data set of the ChainLadder package class(RAA) <- "matrix" # change the class from triangle to matrix df <- as.data.frame(t(RAA)) # coerce triangle into a data.frame names(df) <- 1981 : 1990 df$dev <- 1:10 plot(gvisLineChart(df, "dev", options=list(gvis.editor="Edit me!", hAxis.title="dev. period")))
2 comments :
First of all, I'd like to thank you for such a useful blog. It is highly interesting. Secondly, about the post, you missed one line of R code here. You didn't specify from where RAA was initialized. Could you include that line please?
Thanks!
Thanks for your comment.
I have added the following statement above:
data(RAA)
Although it shouldn't be necessary, as the data is automatically loaded with the ChainLadder package.
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