On April 19th, the seminar series will welcome Prof Refik Soyer, chair of decision sciences and statistics at the George Washington University (GWU) in Washington D.C. Prof Soyer will present work completed jointly with Di Zhang (GWU) and Hedibert Lopes (Arizona State University) introducing a new class of multivariate integer-valued autoregressive models.
Title
Latent Factor Bayesian Multivariate INAR Models
Abstract
We introduce a new class of multivariate integer-valued autoregressive (INAR) models based on the notion of a common random environment. Dependence among the components of the multivariate time series is induced via the common environment that follows a Markovian evolution. The proposed framework provides us with a dynamic multivariate generalization of the univariate INAR processes. We develop a Markov chain Monte Carlo method as well as a particle learning algorithm for Bayesian inference. We consider an extension of the model to handle zero inflated time-series data and illustrate the proposed class of models using actual multivariate count data and discuss their predictive performance.
Biography
Refik Soyer is chair and professor of decision sciences and of statistics at the George Washington University (GW). He is the Mitch Blaser Distinguished Scholar in Business Analytics. He also serves as the director of the Institute for Integrating Statistics in Decision Sciences at GW. He received his DSc in operations research from GW, MSc in operational research from the University of Sussex, England and BA in economics from Bogazici University, Turkey. His area of interests are Bayesian statistics and decision analysis, stochastic modeling, statistical aspects of reliability analysis, and time series analysis. He has published over 100 articles and directed or co-directed 13 doctoral dissertations. His work has appeared in journals such as Journal of the American Statistical Association, Journal of the Royal Statistical Society, Ser. B., Technometrics, Biometrics, Journal of Econometrics, Statistical Science, International Statistical Review, Annals of Applied Statistics and Management Science. He has also co-edited a volume titled Mathematical Reliability: An Expository Perspective. His research was supported by Army Research Office, National Science Foundation and Office of Naval Research. Soyer is an elected member of the International Statistical Institute, Fellow of the Turkish Statistical Association and a Fellow of the American Statistical Association. He was a vice president of the International Association for Statistical Computing. He served on the editorial board of the Journal of the American Statistical Association and is currently an associate editor of the Applied Stochastic Models in Business and Industry.