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VERSION:2.0
CALSCALE:GREGORIAN
PRODID:UW-Madison-Physics-Events
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UID:UW-Physics-Event-4271
DTSTART:20160912T170000Z
DTEND:20160912T180000Z
DTSTAMP:20260416T222252Z
LAST-MODIFIED:20160906T161328Z
LOCATION:2241 Chamberlin Hall
SUMMARY:An Introduction to Bayesian Analysis for Fusion Science\, Plas
 ma Physics (Physics/ECE/NE 922) Seminar\, Lisa Reusch\, UW Madison
DESCRIPTION:The harsh conditions that will exist in fusion devices tha
 t are in full nuclear environments will place severe limits on the dia
 gnostics.  Integrated data analysis (IDA) provides methods to maximize
  the scientific value of the diagnostic data\, and is a growing area o
 f research in the fusion community. The goal of IDA is to combine info
 rmation from different diagnostics to get the most reliable measuremen
 t of physical parameters of interest in a standardized and transparent
  way.  A natural framework in which to develop IDA is Bayesian probabi
 lity theory or Bayesian analysis.  On its own\, Bayesian analysis of a
  diagnostic can offer advantages over traditional approaches to analys
 is\, in particular when the analysis involves complex inversions.  In 
 the context of IDA\, the probabilistic focus of Bayesian analysis allo
 ws an IDA technique to be developed modularly\, one diagnostic at a ti
 me.  It automatically includes error analysis and provides a method fo
 r including background information into the analysis quantitatively. T
 his talk presents an introduction to a Bayesian approach to data analy
 sis using concrete examples. It focuses on explaining the terms in Bay
 es’ Rules\, the foundation for Bayesian analysis\, and will highligh
 t important considerations that need to be made when applying Bayesian
  analysis to a particular diagnostic. Its function as a framework for 
 IDA will also be illustrated.
URL:https://www.physics.wisc.edu/events/?id=4271
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