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Activity Number: 255 - Contributed Poster Presentations: Section on Statistical Computing
Type: Contributed
Date/Time: Monday, July 29, 2019 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Computing
Abstract #306379
Title: Edge Deletion Tests in Graphical Models for Multivariate Time Series
Author(s): Marco Reale* and Chris Price and Anna Lin and Rory Ellis
Companies: University of Canterbury and University of Canterbury and Statistics New Zealand and University of Canterbury
Keywords: Sparsity; VARMA models; Multiple testing; Structural models; Directed acyclic graphs; Conditional independence

A multivariate time series model, of the structural vector auto-regressive moving average type, can be represented by a graphical model where each node is a variable at a time index (t, t-1,... etc). In this context, edges would represent conditional dependence between the connected time series. While a saturated models includes edges between each variable at time t and all the other variables, a parsimonious (sparse) models would have some of the edges deleted. In the research we illustrate different approaches to test for the significance of the presence of the edges and compare them through simulation studies.

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

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