Reply to C. Tsallis' "Conceptual Inadequacy of the Shore and Johnson Axioms for Wide Classes of Complex Systems"

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College of Natual Science and Mathematics, Physics and Astronomy


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 fpig 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.

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