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SUMMARY:The Hardness of Conditional Independence Testing - Jonas Peters (U
 niversity of Copenhagen)
DTSTART:20180115T115500Z
DTEND:20180115T124000Z
UID:TALK97570@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Testing for conditional independence between continuous random
  variables is considered to be a hard statistical problem. We provide a fo
 rmalization of this result and show that a test with correct size does not
  have power against any alternative. It is thus impossible to obtain any g
 uarantee if the relationships between the random variables can be arbitrar
 ily complex. We propose a practical test that achieves the correct size if
  the conditional expectations are smooth enough such that they can be esti
 mated from data. This is joint work with Rajen Shah.
LOCATION:Seminar Room 1\, Newton Institute
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