Preface

Coding sessions for ST429 are included here.

In these programming sessions, we will apply some statistical and computational techniques to practical problems in risk management. Each session is designed to reinforce your understanding of the theoretical concepts by implementing them in R, working through real or simulated data examples.

Getting Started with R

R is a free software environment for statistical analysis and graphical visualisation. You can download R, access its documentation, and find answers to common questions from The R Project for Statistical Computing website. A user-friendly interface, RStudio, is also available as an open-source integrated development environment (IDE) that simplifies working with R.

  1. You will need to have both R and RStudio installed on your computer.

  2. One of the most important packages you should install is library(qrmtools). To install a release version of a package from CRAN a command like install.packages("qrmtools") from inside RStudio will generally work.

  3. The R scripts and packages are under constant development. This might require you to update packages to the latest development versions. For packages developed on R-Forge (development server), this can typically be done with install.packages("qrmtools", repos = "http://R-Forge.R-project.org"). Should there be any problem during the installation, download the source code from this directory and compile. Type ?install.packages at the R command line for more information.