NonGaussian Multivariate Time Series Modeling

Monday, March 20, 2017 - 3:30pm

Refik Soyer, George Washington University


We consider modeling of multivariate nonGaussian time series of correlated observations. In so doing, we focus on time series from the time transformed exponential family of  distributions. Dependence among series arises as a result of sharing a common dynamic environment. We discuss characteristics of the resulting multivariate time series models and develop  Bayesian inference for them using particle filtering and Markov chain Monte Carlo methods. 

Seminars generally take place in 116 Old Chem Building on Fridays from 3:30 - 4:30 pm. However, please check individual abstracts to confirm time and location. Refreshments will be served after the seminars in Old Chemistry 211. Metered Parking is available at various locations on campus. If you have never visited us before, please see our driving directions and map. The easiest and most convenient parking areas are located at the Bryan Center parking garage near Duke Statistics (recommended) or at the Sarah P. Duke Gardens. Please email or call Karen Whitesell for additional information: or phone 919-684-8029. Sorry, but we do not have reprints available. Please feel free to contact the authors by email for follow-up information, articles, etc. Reception following seminar in 211 Old Chemistry

Old Chemistry 116

Location Info