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SUMMARY:Vector Autoregressive based Network Models - George Michailidis (U
 niversity of Florida)
DTSTART:20161216T093000Z
DTEND:20161216T103000Z
UID:TALK69525@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:<span>Vector autoregressions represent a popular class of time
  series models that aim to capture temporal interconnections between tempo
 rally evolving<br></span><span>entities. &nbsp\;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 prese
 ntation\, we discuss modeling and estimation issues in the high dimensiona
 l setting under different constrains<br></span><span>on the transition mat
 rices - sparsity\, low rankness. We also provide extensions to multi-layer
  networks and illustrate the results with application&#x200B\;s<br></span>
 to financial stability monitoring and biological regulation.
LOCATION:Seminar Room 1\, Newton Institute
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