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SUMMARY:A Central Limit Theorem for non identically distributed random var
 iables with an application to Sobol indices
DTSTART:20260528T120000Z
DTEND:20260528T140000Z
DTSTAMP:20260508T205000Z
UID:indico-event-16344@indico.math.cnrs.fr
DESCRIPTION:Speakers: Jérémy Boyer (IMT)\n\nThe Central Limit Theorem (C
 LT) is one of the most well-known results in probability theory. It is tra
 ditionally stated for independent and identically distributed random varia
 bles. In this talk\, I will present a version of the Central Limit Theorem
  where we only keep the independence assumption.This generalization allows
  us to handle heterogeneous frameworks in statistics. I will then establis
 h a connection between this version of the CLT and a classical estimator u
 sed in sensitivity analysis. To this end\, I will introduce Sobol theory f
 rom the beginning\, including Sobol indices and their interpretations\, up
  to the main estimators used in practice. I will conclude my presentation 
 by briefly explaining how the CLT introduced at the beginning can be used 
 to prove the convergence of a particular estimator.\n\nhttps://indico.math
 .cnrs.fr/event/16344/
LOCATION:Johnson (1R3 - 1st floor)
URL:https://indico.math.cnrs.fr/event/16344/
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