Multivariate extremes

Exploring Non-Linear Interactions in Multivariate Time Series

Hernando Ombao, Professor, Statistics

Nov 5, 12:00 - 13:00

KAUST

Linear Multivariate extremes Bayesian computational statistics

Advances in imaging technology have given neuroscientists unprecedented access to examine various facets of how the brain “works”. Brain activity is complex. A full understanding of brain activity requires careful study of its multi-scale spatial-temporal organization (from neurons to regions of interest; and from transient events to long-term temporal dynamics). Motivated by these challenges, we will explore some characterizations of dependence between components of a multivariate time series and then apply these to the study of brain functional connectivity.

Pavel Krupskiy

Postdoctoral Research Fellow, Statistics

copulas Multivariate extremes nonparametric statistics Spatial data

Krupskiy, Pavel Postdoctoral Fellows Ph.D. 2014, University of British Columbia, Canada Now Assistant Professor at University of Melbourne Education Ph.D. in Statistics 2014, University of British Columbia, Canada M.A. in Economics 2009, New Economic School, Russia B.Sc. in Mathematics 2006, Lomonosov Moscow State University, Russia Research interests copulas, multivariate extremes, nonparametric statistics, spatial data