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SUMMARY:An overview of shape-constrained estimation problems - Yining Chen
  (University of Cambridge)
DTSTART:20120312T140000Z
DTEND:20120312T150000Z
UID:TALK35861@talks.cam.ac.uk
CONTACT:Elena Yudovina
DESCRIPTION:Shape-constrained density estimation has received a great deal
  of interest recently. The allure is the prospect of obtaining fully autom
 atic nonparametric estimators with no tuning parameters. The general idea 
 dates back to Grenander (1956)\, who derived the maximum likelihood estima
 tor of a decreasing density on [0\,∞). Some other popular shape-constrai
 nts include convex and log-concave.\n\nIn this talk\, I will give a brief 
 overview of the area\, focusing particularly on the log-concave constraint
  (i.e. the logarithm of the density function is concave). I will also ment
 ion nice applications of this technique in regression problems and time se
 ries analysis. Essential background of nonparametric statistics will also 
 be covered with R demonstrations.
LOCATION:CMS\, MR12
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