Reply to C. Tsallis’ “Conceptual Inadequacy of the Shore and Johnson Axioms for Wide Classes of Complex Systems”
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 nonadditi...
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MDPI AG
2015-07-01
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| Series: | Entropy |
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| Online Access: | http://www.mdpi.com/1099-4300/17/7/5043 |
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doaj-f082ff1e6814412b866601d61f26c51e2020-11-24T23:52:06ZengMDPI AGEntropy1099-43002015-07-011775043504610.3390/e17075043e17075043Reply to C. Tsallis’ “Conceptual Inadequacy of the Shore and Johnson Axioms for Wide Classes of Complex Systems”Steve Pressé0Kingshuk Ghosh1Julian Lee2Ken A. Dill3Department of Physics, Indiana Univ.-Purdue Univ. Indianapolis, Indianapolis, IN 46202, USADepartment of Physics and Astronomy, University of Denver, Denver, CO 80208, USADepartment of Bioinformatics, Soongsil University, Seoul 156-743, KoreaLaufer Center for Physical and Quantitative Biology and Departments of Physics and Chemistry, Stony Brook University, Stony Brook, NY 11794, USAIn 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.http://www.mdpi.com/1099-4300/17/7/5043nonadditive entropiesnonextensive statistical mechanicsstrongly correlated random variablesShore and Johnson axioms |
| collection |
DOAJ |
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English |
| format |
Article |
| sources |
DOAJ |
| author |
Steve Pressé Kingshuk Ghosh Julian Lee Ken A. Dill |
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Steve Pressé Kingshuk Ghosh Julian Lee Ken A. Dill Reply to C. Tsallis’ “Conceptual Inadequacy of the Shore and Johnson Axioms for Wide Classes of Complex Systems” Entropy nonadditive entropies nonextensive statistical mechanics strongly correlated random variables Shore and Johnson axioms |
| author_facet |
Steve Pressé Kingshuk Ghosh Julian Lee Ken A. Dill |
| author_sort |
Steve Pressé |
| title |
Reply to C. Tsallis’ “Conceptual Inadequacy of the Shore and Johnson Axioms for Wide Classes of Complex Systems” |
| title_short |
Reply to C. Tsallis’ “Conceptual Inadequacy of the Shore and Johnson Axioms for Wide Classes of Complex Systems” |
| title_full |
Reply to C. Tsallis’ “Conceptual Inadequacy of the Shore and Johnson Axioms for Wide Classes of Complex Systems” |
| title_fullStr |
Reply to C. Tsallis’ “Conceptual Inadequacy of the Shore and Johnson Axioms for Wide Classes of Complex Systems” |
| title_full_unstemmed |
Reply to C. Tsallis’ “Conceptual Inadequacy of the Shore and Johnson Axioms for Wide Classes of Complex Systems” |
| title_sort |
reply to c. tsallis’ “conceptual inadequacy of the shore and johnson axioms for wide classes of complex systems” |
| publisher |
MDPI AG |
| series |
Entropy |
| issn |
1099-4300 |
| publishDate |
2015-07-01 |
| description |
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. |
| topic |
nonadditive entropies nonextensive statistical mechanics strongly correlated random variables Shore and Johnson axioms |
| url |
http://www.mdpi.com/1099-4300/17/7/5043 |
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