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Activity Number: 43
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #320535
Title: Bayesian Matrix Autoregressive Models
Author(s): Seyed Yaser Samadi* and Lynne Billard
Companies: Southern Illinois University Carbondale and University of Georgia
Keywords: Matrix Times Series ; Bayesian Approach ; Autoregressive Models ; Prior

Many data sets in biology, medicine, economic, business, fMRI and other areas deal with multiple sets of multivariate time series. A class of matrix autoregressive (MAR) models is introduced for dealing with the situation where there are multiple sets of multivariate time series data. However, the large number of the parameters is the main concern with MAR models. To overcome computational constraints, it is desired to use Bayesian approach with prior information to shrink the large number of parameters.

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

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