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Activity Number: 546 - Recent Advances in Time Series and Point Process
Type: Invited
Date/Time: Wednesday, July 31, 2019 : 2:00 PM to 3:50 PM
Sponsor: Business and Economic Statistics Section
Abstract #300536
Title: A Factor Model Approach for High-Dimensional Dynamic Tensor Time Series
Author(s): Rong Chen* and Dan Yang and Cun-Hui Zhang
Companies: Rutgers University and Rutgers University and Rutgers University
Keywords: tensor; time series; factor model; high-dimensional

Modern data collection capabilities have led to massive quantity of time series. Large tensor (or multi-dimensional array) data are now routinely collected in a wide range of applications, and often such observations are taken over time, forming tensor time series. In this talk we present a factor model approach for analyzing high-dimensional dynamic tensor time series. Specifically we develop a general class of tensor factor models, with modifications for specific applications, in modeling matrix- and tensor-valued time series and dynamic networks. Estimation procedures along with their theoretical properties, numerical results and applications will be presented.

Authors who are presenting talks have a * after their name.

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