Longevity and mortality dynamics with R
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Following the previous post on life contingencies and actuarial models in life insurance, I upload additional material for the short course at the 6th R/Rmetrics Meielisalp Workshop & Summer School on Computational Finance and Financial Engineering organized by ETH Zürich, https://www.rmetrics.org/. The second part of the talk (on Actuarial models with R) will be dedicated to longevity and mortality. A complete set of slides can be downloaded from the blog, but again, only some part will be presented.
As mentioned earlier, the codes are from a book on actuarial science in R, written with Christophe Dutang (so far in French) that should appear, some day… The code used in the slides above can be downloaded from here, and datasets are the following,
> DEATH <- read.table( + "http://freakonometrics.free.fr/Deces-France.txt", + header=TRUE) > EXPO <- read.table( + "http://freakonometrics.free.fr/Exposures-France.txt", + header=TRUE,skip=2)
For additional resources, I will use Rob Hyndman‘s package on demography, Heather Turner and David Firth’s package on generalized nonlinear models (e.g. the slides of the short course Heather gave in Rennes at the UseR! conference in 2009), as well as functions developed by JPMorgan’s LifeMetrics (functions are fully documented in the LifeMetrics Technical Document). All those functions can be obtained using
> library(demography) > library(gnm) > source("http://freakonometrics.free.fr/fitModels.R")
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.