Interactive presentations with deck.js
Data analysis is often an iterative and interactive process. However, when I present about this subject, I feel often limited by the presentation software I use. It doesn't matter if I use LaTeX/PDF, PowerPoint or Keynote. In all cases it is either very difficult or impossible to include interactive charts, such as Flash or SVG charts. As a result I have to switch between various applications during the talk. This can be fun, but quite often it is not.The other day I came across a presentation by Christopher Gandrud. Christopher had used deck.js, a JavaScript library for building HTML presentations by Caleb Troughton.
This looked like an interesting approach to me and fortunately the learning curve was not too steep, although I am by no means an html or JavaScript expert. So I created my first deck.js presentation based on the content of previous googleVis presentations. For the first time I can embed videos, Flash and SVG charts without using lots of different apps. I am actually quite pleased by the result, see here: Getting started with googleVis
Stochastic reserving with R: ChainLadder 0.1.51 released
Today we published version 0.1.51 of theChainLadder
package for R. It provides methods which are typically used in insurance claims reserving to forecast future claims payments.Claims development and chainladder forecast of the RAA data set using the Mack method 
Initially the package came with implementations of the Mack, Munich and Bootstrap ChainLadder methods. Since version 0.1.33 it also provides general multivariate chain ladder models by Wayne Zhang. Version 0.1.40 introduced new functions on loss development factor fitting and Cape Cod by Daniel Murphy following a paper by David Clark. Version 0.1.50 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 0.1.51:
 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")))
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