Home Page

Papers

Submissions

News

Scope

Editorial Board

Announcements

Proceedings

Open Source Software

Search

Login



RSS Feed

Tractable Bayesian Inference of Time-Series Dependence Structure

Michael Siracusa, John Fisher III; JMLR W&CP 5:528-535, 2009.

Abstract

We consider the problem of Bayesian inference over graphical structures describing the interactions among multiple vector time-series. A directed temporal interaction model is presented which assumes a fixed dependence structure among time-series. Using a conjugate prior over this model's structure and parameters, we focus our attention on characterizing the exact posterior uncertainty in the structure given data. The model is extended via the introduction of a dynamically evolving latent variable which indexes dependence structures over time. Performing inference using this model yields promising results when analyzing the interaction of multiple tracked moving objects.



Home Page

Papers

Submissions

News

Scope

Editorial Board

Announcements

Proceedings

Open Source Software

Search

Login



RSS Feed

Page last modified on Fri Apr 3 20:30:46 BST 2009.

Copyright @ JMLR 2000. All rights reserved.