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Reply to C. Tsallis’ “Conceptual Inadequacy of the Shore and Johnson Axioms for Wide Classes of Complex Systems”

By Steve Pressé, Kingshuk Ghosh, Julian Lee and Ken A. Dill

Abstract

In a recent PRL (2013, 111, 180604), we invoked the Shore and Johnson axioms which demonstrate that the least-biased way to infer probability distributions {pi} from data is to maximize the Boltzmann-Gibbs entropy. We then showed which biases are introduced in models obtained by maximizing nonadditive entropies. A rebuttal of our work appears in entropy (2015, 17, 2853) and argues that the Shore and Johnson axioms are inapplicable to a wide class of complex systems. Here we highlight the errors in this reasoning

Topics: nonadditive entropies, nonextensive statistical mechanics, strongly correlated random variables
Publisher: 'MDPI AG'
Year: 2015
DOI identifier: 10.3390/e17075043.
OAI identifier: oai:scholarworks.iupui.edu:1805/8982
Provided by: IUPUIScholarWorks

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