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SUMMARY:Metamodels and the Bootstrap for Input Model Uncertainty Analysis 
 - Barton\, R (National Science Foundation)
DTSTART:20110908T103000Z
DTEND:20110908T110000Z
UID:TALK32716@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:The distribution of simulation output statistics includes vari
 ation form the finiteness of samples used to construct input probability m
 odels. Metamodels and bootstrapping provide a way to characterize this err
 or. The metamodel-fiting experiment benefits from a sequential design stra
 tegy. We describe the elements of such a strategy\, and show how they impa
 ct performance.\n
LOCATION:Seminar Room 1\, Newton Institute
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