by Katrien Antonio and Jonas Crevecoeur and Jens Robben
Course materials for the Loss Models Computer Labs in December 2024.
📆 December, 2024
⏲ From 11 am to 1 pm
📌 online
Course materials will be posted in the days before the lectures.
This series of lectures introduces the essential concepts of building insurance loss models with R. You will gain insights in the foundations of handling loss data, including useful data wrangling and visualization steps. You will cover a variety of discrete and continuous loss distributions, and techniques to build more flexible distributions from standard distributions (by mixing and splicing). You will learn how to fit these models to actual data and inspect their goodness-of-fit. Then, you will use the fitted model to estimate risk measures. You will acquire insights in the foundations of these analytic methods, learn how to set-up the model building process, and focus on building a good understanding of the resulting model output and predictions.
Leaving this workshop, you should have a firm grasp of the working principles of a variety of loss models for frequency and severity data and be able to explore their use in practical settings. Moreover, you should have acquired the fundamental insights to explore some other methods on your own.
The detailed schedule is subject to small changes.
| Session | Duration | Description | Lecture material |
|---|---|---|---|
| Day 0 | your own pace | Prework | sheets prework in html and in pdf |
| December 14 & 16 | sheets in html and in pdf |
Topics include:
- data sets used in the course: MTPL and SecuraRe losses
- data handling and visualization tools with {ggplot} and {dplyr}
- building frequency models: Poisson, Negative Binomial, ZI and Hurdle, maximum likelihood estimation and goodness-of-fit
- building severity models: simple to complex parametric distributions, splicing to construct a global fit, mixing, estimate a risk measure.
Download lecture sheets in html and pdf.
An excellent collection of tutorials, books, workshops, events is available via
http://www.actuarialdatascience.org
The workshop requires a basic understanding of R. We prepared some prework sheets that you can take a look at before the workshop (html or pdf). Yet another good starting level is the material covered in the 1-Basic folder of the Programming in R workshop taught at Nationale Nederlanden in June 2019.
Being familiar with statistical or machine learning methods is not required. The workshop gradually builds up these concepts, with an emphasis on hands-on demonstrations and exercises.
You have two options to join the coding exercises covered during the workshop. Either you join the RStudio cloud workspace dedicated to the workshop, and then you’ll run R in the cloud, from your browser. Or you use your local installation of R and RStudio.
If you prefer not to work with a local installation of R (and the necessary packages), you can join our workspace on R Studio Cloud. This should be a very accessible set-up for working with R in the cloud for the less experienced user!
Here are the steps you should take (before the workshop):
[no longer valid, please download the material from GitHub, eg using the green button on top of the repo]
- visit the above link
- log in by creating an account for RStudio or by using your Google or GitHub login credentials
- join the space
- at the top of your screen you see ‘Projects’, click ‘Projects’
- with the ‘copy’ button (on the right) you can make your own version of the ‘December 14 & 16’ project; in this copy you can work on the exercises, add comments etc.
- you should now be able to visit the project and see the ‘scripts’ and ‘data’ folders on the right. Open and run the ‘installation-instructions.R’ script from the scripts folder, to see if everything works fine.
We will have everything set up for you in the correct way. You only have to login and open your copy of the project!
Please bring a laptop with a recent version of R and RStudio installed. Make sure you can connect your laptop to the internet (or download the course material one day before the start of the workshop). You will need:
- R (at least 3.5.2 https://cloud.r-project.org/bin/windows/base/)
- RStudio (https://www.rstudio.com/products/rstudio/download/#download)
Please run the following script in your R session to install the required packages
packages <- c("tidyverse", "here", "gridExtra", "grid", "rstudioapi", "MASS", "actuar", "statmod", "ReIns", "pscl")
new_packages <- packages[!(packages %in% installed.packages()[,"Package"])]
if(length(new_packages)) install.packages(new_packages)
if(sum(!(packages %in% installed.packages()[, "Package"]))) {
stop(paste('The following required packages are not installed:\n',
paste(packages[which(!(packages %in% installed.packages()[, "Package"]))], collapse = ', ')));
} else {
message("Everything is set up correctly. You are ready to go.")
}
Katrien Antonio is professor in insurance data science at KU Leuven and professor in insurance data science at University of Amsterdam. She teaches courses on data science for insurance, life and non-life insurance mathematics and loss models. Research-wise Katrien puts focus on pricing, reserving and fraud analytics, as well as mortality dynamics.
Happy learning!