- Title
- Equidistribution testing with Bayes factors and the ECT
- Creator
- Stokes, Barrie; Tuyl, Frank; Hudson, Irene
- Relation
- Bayesian Inference and Maximum Entropy Methods in Science and Engineering: 35th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIP Conference Proceedings, Volume 1757 (Postdam, NY 19-24 July, 2015)
- Publisher Link
- http://dx.doi.org/10.1063/1.4959055
- Publisher
- AIP Publishing
- Resource Type
- conference paper
- Date
- 2016
- Description
- John Skilling’ s Nested Sampling algorithm is a numerical method for fitting models to data in the Bayesian setting, producing estimates of the Bayesian Evidence Z and Information ℋ as well as posterior samples. A central step in the process is the generation of a new random sample from the (typically uniform) prior distribution subject to the constraint that the new prior sample’s likelihood is greater than a current likelihood threshold. One way to test a generation method - the “outside in” approach - is to incorporate it in a Nested Sampling algorithm and compare the resulting model estimates with known cases. Another way - the “inside out” approach - is to validate the uniformity of prior samples produced by the new method before its incorporation in a Nested Sampling system. Using the “inside out” approach, we show that E T Jaynes’ Entropy Concentration Theorem (ECT) and a Bayes Factor test of a particular type provide sensitive tests of uniformity in irregular 2D regions.
- Subject
- testing procedures; computer modeling; entropy
- Identifier
- http://hdl.handle.net/1959.13/1324642
- Identifier
- uon:25083
- Identifier
- ISBN:9780735414150
- Rights
- The version of record: Barrie Stokes(a), Frank Tuyl, and Irene Hudson "Equidistribution testing with Bayes factors and the ECT" AIP Conference Proceedings 2016 1757:1 is available at http://doi.org/10.1063/1.4959055
- Language
- eng
- Full Text
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