Abstract Details
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Activity Number:
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503
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract #312542
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View Presentation
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Title:
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Exploring Minimaxity and Admissibility of the Usual Estimates and Usual Confidence Sets for the Means of Selected Populations
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Author(s):
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Alexandra Bolotskikh*+ and Martin Wells
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Companies:
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Cornell University and Cornell University
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Keywords:
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Mean estimation ;
post-selection inference ;
minimaxity ;
admissibility
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Abstract:
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Researchers are often interested in making inference for one or a few "best" out of many treatments - this problem is referred to as inference after selection. Substantial research has been done on constructing point estimates and confidence sets for a multivariate normal mean vector, but there are very few results on post-selection point estimates and confidence sets. In this talk we provide a complete overview for minimaxity and admissibility of the usual point estimates and confidence sets for the mean estimation of a normal distribution after selection. We will highlight the past, state of the art, and possible future research results for post-selection inference.
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Authors who are presenting talks have a * after their name.
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