A note on Bayes empirical Bayes estimation by means of Dirichlet processes |
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| Affiliation: | 1. State University of New York, Stony Brook, NY, USA;2. University of California at Davis, CA, USA;1. Department of Mathematics, the Pennsylvania State University, 109 McAllister Building, University Park, PA 16802-6400, USA;2. Department of Meteorology and Atmospheric Science, the Pennsylvania State University, 503 Walker Building, University Park, PA 16802-5013, USA;3. Institute for CyberScience, the Pennsylvania State University, 224B Computer Building, University Park, PA 16802, USA;1. Ruhr-Universität Bochum, Fakultät für Mathematik, 44780 Bochum, Germany;2. Department of Economics, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA 02467, USA;3. University of Hamburg, Department of Mathematics, Bundesstrasse 55, 20146 Hamburg, Germany |
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| Abstract: | Bayes estimators are derived by means of the Dirichlet process hyperprior approach for general empirical Bayes problems. For any sample size, these estimators are expressed concisely as ratios of two multidimensional integrals. A numerical example on Poisson sampling is given. |
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