Nonparametric Copula Day
June 12, 2015
Over the last decades dependence modeling with copulas has become a popular tool in modern statistics. Copulas are now widely applied in fields such as finance, insurance and hydrology. In recent years, nonparametric methods for copula modeling are gaining momentum, since their flexibility enables to identify and capture even the most complex dependence patterns.
This workshop showcases recent developments related to nonparametric inference for copula functions with topics ranging from estimation to model selection. Its goal is to gather some of the most active researchers in the field in order to identify upcoming challanges, inspire new ideas, and initiate collaboration.
|09:00 - 09:15||Welcome|
|09:15 - 10:00|| Irene Gijbels:
"Nonparametric testing for no covariate effects in conditional copulas"
|10:00 - 10:45|| Christian Schellhase:
"Estimation of Non-Simplified Vines Using Nonparametric Trivariate Copula Constructions"
|10:45 - 11:15||Coffee break|
|11:15 - 12:00|| Thomas Nagler:
"Evading the curse of dimensionality in multivariate kernel density estimation with simplified vines"
|12:00 - 13:30||Lunch break|
|13:30 - 14:15|| Gerda Claeskens:
"Copula Directed Acyclic Graphs"
|14:15 - 15:00|| Artem Prokhorov:
"Copula based factorization in Bayesian multivariate infinite mixture models"
|15:00 - 15:30||Coffee break|
|15:30 - 16:15|| Xue Wang:
"Bayesian nonparameteric inference for a multivariate copula function"
|16:15 - 17:00||Poster session|
There will be an optional (self-pay) dinner on Thursday evening and a visit to a beer garden on Friday evening after the end of the workshop.