BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//talks.cam.ac.uk//v3//EN
BEGIN:VTIMEZONE
TZID:Europe/London
BEGIN:DAYLIGHT
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:BST
DTSTART:19700329T010000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
TZNAME:GMT
DTSTART:19701025T020000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
CATEGORIES:Statistics
SUMMARY:Local Independence Graphs - Niels Richard Hansen (
University of Copenhagen)
DTSTART;TZID=Europe/London:20221104T140000
DTEND;TZID=Europe/London:20221104T150000
UID:TALK182726AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/182726
DESCRIPTION:Conditional local independence\, or Granger non-ca
usality\, is a notion of conditional independence
among coordinates of a multivariate stochastic pro
cess. Local independence graphs can be used to enc
ode such conditional local independencies\, and th
e abstract and asymmetric independence models enco
ded by directed\, and possibly cyclic graphs\, are
of intrinsic interest.\n\nIn the talk I will intr
oduce conditional local independence and local ind
ependence graphs via a classical example of a time
homogeneous multivariate Markov process with bina
ry coordinates. This will illustrate how local ind
ependence graphs relate to classical graphical mod
els\, such as the Ising model\, but also how they
generalize such\nmodels by allowing for an asymmet
ric dependence over time. I will then show some of
the main results we know about local independence
graphs\, such as marginalization operations and a
characterization of Markov equivalence classes\,
and I will outline how local independence graphs c
an be learned via conditional local independence t
esting.
LOCATION:MR12\, Centre for Mathematical Sciences
CONTACT:Qingyuan Zhao
END:VEVENT
END:VCALENDAR