Date: 2017-01-27

Time: 15:30-16:30

Location: ROOM 6254 Pavillon Andre-Aisenstadt 2920, UdeM

Abstract:

Conditional copula models describe dynamic changes in dependence and are useful in establishing high dimensional dependence structures or in joint modelling of response vectors in regression settings. We describe some of the methods developed for estimating the calibration function when multiple predictors are needed and for resolving some of the model choice questions concerning the selection of copula families and the shape of the calibration function. This is joint work with Evgeny Levi, Avideh Sabeti and Mian Wei.

Speaker

Radu Craiu is Professor of Statistics in the Department of Statistical Sciences at University of Toronto.