Dates: 13-14 December 2017.
Venue: Clore Management Centre, Birkbeck University of London.
Room: CLO B01
Link with tutorials: Modules II and III will constitute the tutorials of the joint CFE-CMStatistics conference. Participants to the conference can register separately for the tutorials and for Module I.
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
PhD students and Early Career Investigators (who have obtained their PhD degree in 2010 or after) can apply for a limited number of grants of 500 Euro for accommodation and traveling and will have their fees for the course waived.
Organized by the CRoNos COST Action IC1408 represented by
Erricos J. Kontoghiorghes and Ana Colubi.
Sponsored by COST
Wednesday, 13 December 2017
Thursday, 14 December 2017
Summary: Copulas are multivariate distribution functions with standard uniform univariate margins. They are increasingly applied to modeling 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 this short course is to introduce the main theoretical results about copulas and to show how statistical modeling of multivariate continuous distributions using copulas can be carried out in the R statistical environment.
Sessions 1.1 and 1.2: Basic introduction to copulas and their main properties, along with the most important theoretical results.
Session 1.3: The most widely used copula classes, their corresponding sampling procedures, along with selected copula transformations that are important for practical purposes.
Sessions 1.4 and 1.5: Estimation of copulas from a parametric, semi-parametric and non-parametric perspective.
Sessions 1.6 and 1.7: Graphical diagnostics, statistical tests and model selection.
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 or vine copulas are not covered.