Renyi entropy violates the Shore-Johnson subset-independence axiom, so using it for maximum-entropy inference with linear constraints introduces biases not present in the data.
Comment on "R\'enyi entropy yields artifficial biases not in the data and incorrect updating due to the infinite-size data"
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abstract
In their recent paper [Phys. Rev. E 99 (2019) 032134], T. Oikinomou and B. Bagci have argued that R\'enyi entropy is ill-suited for inference purposes because it is not consistent with the Shore{ Johnson axioms of statistical estimation theory. In this Comment we seek to clarify the latter statement by showing that there are several issues in Oikinomou{Bagci reasonings which lead to erroneous conclusions. When all these issues are properly accounted for, no violation of Shore- Johnson axioms is found.
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Renyi entropy violates the Shore-Johnson subset-independence axiom, so using it for maximum-entropy inference with linear constraints introduces biases not present in the data.