Reply to C. Tsallis' "conceptual inadequacy of the Shore and Johnson axioms for wide classes of complex systems"

Steve Presse; Kingshuk Ghosh; Julian Lee; Ken A. Dill

doi:10.3390/e17075043

Reply to C. Tsallis' "conceptual inadequacy of the Shore and Johnson axioms for wide classes of complex systems"

Steve Presse, Kingshuk Ghosh, Julian Lee, Ken A. Dill

Research output: Contribution to journal › Article › peer-review

16 Scopus citations

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 {p_i} 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.

Original language	English (US)
Pages (from-to)	5043-5046
Number of pages	4
Journal	Entropy
Volume	17
Issue number	7
DOIs	https://doi.org/10.3390/e17075043
State	Published - 2015
Externally published	Yes

Keywords

Nonadditive entropies
Nonextensive statistical mechanics
Shore and Johnson axioms
Strongly correlated random variables

ASJC Scopus subject areas

Physics and Astronomy(all)

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10.3390/e17075043

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title = "Reply to C. Tsallis' {"}conceptual inadequacy of the Shore and Johnson axioms for wide classes of complex systems{"}",

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.",

keywords = "Nonadditive entropies, Nonextensive statistical mechanics, Shore and Johnson axioms, Strongly correlated random variables",

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AU - Presse, Steve

AU - Ghosh, Kingshuk

AU - Lee, Julian

AU - Dill, Ken A.

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

KW - Nonadditive entropies

KW - Nonextensive statistical mechanics

KW - Shore and Johnson axioms

KW - Strongly correlated random variables

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Reply to C. Tsallis' "conceptual inadequacy of the Shore and Johnson axioms for wide classes of complex systems"

Abstract

Keywords

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