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Abstract Details
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Activity Number:
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479
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Type:
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Invited
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Date/Time:
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Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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International Society of Bayesian Analysis
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| Abstract - #303828 |
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Title:
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Bayesian Estimation of Intensity Surfaces on the Sphere via Needlet Shrinkage and Selection
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Author(s):
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James G Scott*+
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Companies:
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The University of Texas at Austin
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Address:
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1 University Station, Austin, TX, 78712,
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Keywords:
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needlets ;
shrinkage estimation ;
spherical wavelets
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Abstract:
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This paper describes an approach for Bayesian modeling in spherical data sets. Our method is based upon a recent construction called the needlet, which is a particular form of spherical wavelet with many favorable statistical and computational properties. We perform shrinkage and selection of needlet coefficients, focusing on two main alternatives: empirical-Bayes thresholding, and Bayesian local shrinkage rules. We study the performance of the proposed method- ology both on simulated data and on two real data sets: one involving the cosmic microwave background radiation, and one involving the reconstruction of a global news intensity surface inferred from published Reuters articles in August, 1996. The fully Bayesian approach based on robust, sparse shrinkage priors seems to outperform other alternatives.
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Authors who are presenting talks have a * after their name.
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