Abdul Hadi Asfarangga, The University of Adelaide
Professor Ivan Kojadinovic, University of Pau, France
Copulas are multivariate distribution functions with standard uniform univariate margins. They are increasingly applied to modelling dependence among random variables in probabilistic and statistical models arising in fields such as risk management, actuarial science, insurance, finance, engineering, hydrology, climatology, meteorology, to name a few. The aim of the course is to introduce the main theoretical results about copulas and to show how statistical modelling of multivariate continuous distributions using copulas can be carried out in the R statistical environment.
All the presented concepts will be illustrated by stand-alone and reproducible R examples involving either synthetic or real data. Advanced topics such as dynamic copula models are not covered. This course is based on the book https://www.springer.com/fr/book/9783319896342.
This is intended to be a foundational course for students.
Participants will be expected to have their own laptop with the latest versions of R and the R packages copula, mvtnorm, nor1mix, qrmtools, qrng, MASS, bbmle, latticeExtra, xts, npcp, rugarch, copulaData and lattice installed.
A link with some material will be provided to the students.
This course is based on the book https://www.springer.com/fr/book/9783319896342.
Take this quiz and look at some of the expected foundational skills in this topic