dorsal/arxiv
View SchemaEntropic Priors
| Authors | Ariel Caticha, Roland Preuss |
|---|---|
| Categories | |
| ArXiv ID | physics/0312131 |
| URL | https://arxiv.org/abs/physics/0312131 |
| DOI | 10.1063/1.1751380 |
Abstract
The method of Maximum (relative) Entropy (ME) is used to translate the information contained in the known form of the likelihood into a prior distribution for Bayesian inference. The argument is guided by intuition gained from the successful use of ME methods in statistical mechanics. For experiments that cannot be repeated the resulting "entropic prior" is formally identical with the Einstein fluctuation formula. For repeatable experiments, however, the expected value of the entropy of the likelihood turns out to be relevant information that must be included in the analysis. As an example the entropic prior for a Gaussian likelihood is calculated.
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"abstract": "The method of Maximum (relative) Entropy (ME) is used to translate the\ninformation contained in the known form of the likelihood into a prior\ndistribution for Bayesian inference. The argument is guided by intuition gained\nfrom the successful use of ME methods in statistical mechanics. For experiments\nthat cannot be repeated the resulting \"entropic prior\" is formally identical\nwith the Einstein fluctuation formula. For repeatable experiments, however, the\nexpected value of the entropy of the likelihood turns out to be relevant\ninformation that must be included in the analysis. As an example the entropic\nprior for a Gaussian likelihood is calculated.",
"arxiv_id": "physics/0312131",
"authors": [
"Ariel Caticha",
"Roland Preuss"
],
"categories": [
"physics.data-an",
"physics.comp-ph"
],
"doi": "10.1063/1.1751380",
"title": "Entropic Priors",
"url": "https://arxiv.org/abs/physics/0312131"
},
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