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DTSTART:19700329T010000
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CATEGORIES:Statistics
SUMMARY:Choosing a good histogram - Yannick Baraud (Univ. 
  Nice)
DTSTART;TZID=Europe/London:20091016T160000
DTEND;TZID=Europe/London:20091016T170000
UID:TALK20008AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/20008
DESCRIPTION:Histograms are probably among the most\nsimple and
  popular estimators. They are\nwidely used in scie
 nce\, especially\nby non-statisticians\, in view o
 f estimating\ndensities (or intensities of point p
 rocesses).\nTo build a good histogram\, one needs\
 nto partition the data in a suitable way\nwhich tu
 rns out to be a tricky problem. Given a\n(possibly
  large) family of candidate\npartitions\, how can 
 we select a suitable one\non which our histogram w
 ill be as close as\npossible to  the unknown densi
 ty?\nBesides\, are there families of partitions\no
 ne should consider preferably? These\nare some of 
 the questions we shall try\nto answer in this talk
  by adopting a\nnon-asymptotic point of view.\n\n
LOCATION:MR12\, CMS\, Wilberforce Road\, Cambridge\, CB3 0W
 B
CONTACT:Richard Nickl
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