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DTSTART:20240310T070000
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DTSTART:20231105T060000
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DTSTART;TZID=America/Toronto:20241017T160000
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URL:https://uwaterloo.ca/statistics-and-actuarial-science/events/david-spro
 tt-distinguished-lecture-paul-gustafson
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West Room: DC 1302 Waterloo ON N2L 3G1 Canada
SUMMARY:David Sprott Distinguished Lecture by Paul Gustafson
CLASS:PUBLIC
DESCRIPTION:Distinguished Lecture Series\n\nPAUL GUSTAFSON\n_Department of 
 Statistics at the University of British Columbia_\n\nRoom: DC 1302\n\n----
 ---------------------\n\nBAYESIAN INFERENCE WHEN PARAMETER IDENTIFICATION 
 IS LACKING: A\nNARRATIVE ARC ACROSS APPLICATIONS\, METHODS\, AND THEORY\n\
 nPartially identified models generally yield “in between”\nstatistical
  behavior. As the sample size goes to infinity\, the\nposterior distributi
 on on the target parameter heads to a distribution\nnarrower than the prio
 r distribution but wider than a single point.\nSuch models arise naturally
  in many areas\, including the health\nsciences.  They arise particularly
   when we own up to limitations in\nhow data are acquired.   I aim to h
 ighlight the narrative arc\nassociated with partial identification.   Th
 is runs from the applied\n(e.g.\, broaching the topic with subject-area sc
 ientists)\, to the\nmethodological (e.g.\, implementing a Bayesian analysi
 s without full\nidentification)\, to the theoretical (e.g.\, characterizin
 g what is\ngoing on as generally as possible).  As per many areas of stat
 istics\,\nthere is good scope to get involved across the whole arc\, rathe
 r than\njust at one end or other.
DTSTAMP:20260410T173218Z
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