Maximum Entropy Principle in Statistical Inference: Case for Non-Shannonian Entropies.

08:00 EDT 29th March 2019 | BioPortfolio

Summary of "Maximum Entropy Principle in Statistical Inference: Case for Non-Shannonian Entropies."

In this Letter, we show that the Shore-Johnson axioms for the maximum entropy principle in statistical estimation theory account for a considerably wider class of entropic functional than previously thought. Apart from a formal side of the proof where a one-parameter class of admissible entropies is identified, we substantiate our point by analyzing the effect of weak correlations and by discussing two pertinent examples: two-qubit quantum system and transverse-momentum behavior of hadrons in high-energy proton-proton collisions.


Journal Details

This article was published in the following journal.

Name: Physical review letters
ISSN: 1079-7114
Pages: 120601


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