A minimally informative likelihood approach to Bayesian inference and decision analysis
For a given prior density, we minimize the Shannon Mutual Information between a parameter and the data, over a class of likelihoods defined by bounding a Bayes risk by a 'distortion parameter'. This gives a conditional distribution for the data given the parameter which provides optimal da...
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| Format: | Others |
| Language: | English |
| Published: |
2009
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| Online Access: | http://hdl.handle.net/2429/7313 |
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