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Activity Number: 587
Type: Invited
Date/Time: Wednesday, August 3, 2016 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract #318340
Title: A Nonparametric Rao-Blackwell Theorem with Application to Selective Inference
Author(s): Dennis Sun*
Companies: Cal Poly/Google

The Rao-Blackwell theorem says that an estimator can be improved by conditioning on a sufficient statistic. In this talk, I examine a nonparametric version of the Rao-Blackwell theorem. I show how it can be used to improve estimators derived from data splitting, which are selectively valid but suboptimal (since they do not make use of all of the data).

Authors who are presenting talks have a * after their name.

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