Vector Autoregressive based Network Models

Add to your list(s) Download to your calendar using vCal

• George Michailidis (University of Florida)
• Friday 16 December 2016, 09:30-10:30
• Seminar Room 1, Newton Institute.

If you have a question about this talk, please contact INI IT.

SNAW04 - Dynamic networks

Vector autoregressions represent a popular class of time series models that aim to capture temporal interconnections between temporally evolving
entities.  They have been widely used in macroeconomic and financial modeling and more recently they have found novel applications in functional genomics and neuroscience. In this presentation, we discuss modeling and estimation issues in the high dimensional setting under different constrains
on the transition matrices – sparsity, low rankness. We also provide extensions to multi-layer networks and illustrate the results with application​s
to financial stability monitoring and biological regulation.

This talk is part of the Isaac Newton Institute Seminar Series series.

This talk is included in these lists:

• All CMS events
• Cambridge Centre for Data-Driven Discovery (C2D3)
• Cambridge talks
• Chris Davis' list
• Featured lists
• INI info aggregator
• Interested Talks
• Isaac Newton Institute Seminar Series
• School of Physical Sciences
• Seminar Room 1, Newton Institute
• Trust & Technology Initiative - interesting events
• bld31
• ndk22's list
• ob366-ai4er
• rp587

Note that ex-directory lists are not shown.