Comparison of Minimum Cross-Entropy Inference with Minimally Informative Information Systems
The Minimum Cross-Entropy (MXE) inference rule leads to information systems which are inconsistent, and which may have an expectation less than the prior. The Min-Score rule (a generalization of maximum entropy) applied to information systems generates consistent systems and has a guaranteed expectation at least as great as the prior. The guaranteed expectation for the Min-Score rule is always at least as great as that for MXE.
KeywordsPrior Probability Maximum Entropy Bayesian Method Inference Rule Inductive Inference
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- Dalkey, N. C. (1983). Updating Inductive Inference, presented at the third Workshop on Maximum Entropy and Bayesian Methods in Applied Statistics, University of Wyoming, August 1–4.Google Scholar
- Dalkey, N. C. (1985). Inductive Inference and the Maximum Entropy Principle. In Maximum Entropy and Bayesian Methods in Inverse Problems, eds. C. Ray Smith and W. T. Grandy, pp. 351–64. Dordrect/Boston/Lancaster: D. Reidel.Google Scholar
- Shore, J. E. & Johnson, R. W. (1981) Properties of Cross-Entropy Minimization. IEEE Transactions on Information Theory, IT-27, 472–82.Google Scholar