Sometimes I think “Web Archaeology” ought to be a recognized discipline. There are some real treasures to be found in long-abandoned websites, with just a little exploration.
For example, today I stumbled on the website for “R Souls“, a user group devoted to the actuarial uses of R at Lloyds of London. Seems like it hasn’t been active for a few years. (I resisted the temptation to edit the wiki page to change the name to “Lost R Souls”.) Nonetheless, it looks like they had an interesting series of meetings back in 2006 and took good notes. You can still see some useful examples of R for actuarial analysis, including curve-fitting and fitting censored distributions.
One of the group’s members, Nigel De Silva, also wrote a useful document: A introduction to R: Examples for Actuaries. The first part of the document is your typical introduction to R syntax and objects (albeit using actuarial data for the examples), but it’s the last dozen pages that may be of particular interest, with detailed worked examples from the actuarial field. There are examples on examining and fitting distributions, modeling extreme value distributions, and fitting GLMs for stochastic reserving. …
Sometimes I think “Web Archaeology” ought to be a recognized discipline. There are some real treasures to be found in long-abandoned websites, with just a little exploration.
For example, today I stumbled on the website for “R Souls“, a user group devoted to the actuarial uses of R at Lloyds of London. Seems like it hasn’t been active for a few years. (I resisted the temptation to edit the wiki page to change the name to “Lost R Souls”.) Nonetheless, it looks like they had an interesting series of meetings back in 2006 and took good notes. You can still see some useful examples of R for actuarial analysis, including curve-fitting and fitting censored distributions.
One of the group’s members, Nigel De Silva, also wrote a useful document: A introduction to R: Examples for Actuaries. The first part of the document is your typical introduction to R syntax and objects (albeit using actuarial data for the examples), but it’s the last dozen pages that may be of particular interest, with detailed worked examples from the actuarial field. There are examples on examining and fitting distributions, modeling extreme value distributions, and fitting GLMs for stochastic reserving. The data and scripts are also available for download.
R Toolkit: R Examples for Actuaries