Date: 2014-12-05

Time: 15:30-16:30

Location: BURN 1205

Abstract:

Copula model selection is an important problem because similar but differing copula models can offer different conclusions surrounding the dependence structure of random variables. Chen & Fan (2005) proposed a model selection method involving a statistical hypothesis test. The hypothesis test attempts to take into account the randomness of the AIC and other likelihood-based model selection methods for finite samples. Performance of the test compared to the more common approach of AIC is illustrated in a series of simulations.

Speaker

Julien Roger is an MSc student in the Department of Mathematics and Statistics at McGill University.