A Justification for Applying the Principle of Minimum Relative Entropy to Information Integration Problems

DOI10.1080/01966324.1993.10737344zbMath0789.62004OpenAlexW2004529215WikidataQ58274893 ScholiaQ58274893MaRDI QIDQ4280084

Donald E. Brown

Publication date: 14 March 1994

Published in: American Journal of Mathematical and Management Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01966324.1993.10737344

zbMATH Keywords

Dirichlet priormaximum likelihoodinformation integrationasymptotic equivalenceBayes estimateprinciple of minimum relative entropy

Mathematics Subject Classification ID

Bayesian inference (62F15) Bayesian problems; characterization of Bayes procedures (62C10) Statistical aspects of information-theoretic topics (62B10)

Cites Work

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• I-divergence geometry of probability distributions and minimization problems
• Evaluation of Porter's constant
• A comparison of the Shannon and Kullback information measures
• Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy
• Assessing Risks Through the Determination of Rare Event Probabilities

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