回复“评论”雷尼熵产生人为的偏见，而不是在数据和不正确的更新，由于有限大小的数据““
Reply to "Comment on `Rényi entropy yields artificial biases not in the data and incorrect updating due to the finite-size data' "
摘要：
我们回答Jizba和Korbel的评论[arXiv：1905.00729v1]，首先指出他们提出的Schur-Schurt方法不能确定最佳概率分布的归一化的正确区间，即使归一化是熵最大化过程中的一个必要成分。其次，他们对子集独立公理的处理需要修改拉格朗日乘子，从而使优化不那么可信。我们还明确证明了雷尼熵违反子集独立公理，并将其与香农熵进行比较。第三，Jizba和Korbel提供的新的组成规则，以产生概率分布，即使不需要熵最大化的过程中，在数据中创建人为的偏见为代价。
英文摘要：
We reply to the Comment by Jizba and Korbel [arXiv:1905.00729v1] by first pointing out that the Schur-concavity proposed by them falls short of identifying the correct intervals of normalization for the optimum probability distribution even though normalization is a must ingredient in the entropy maximization procedure. Secondly, their treatment of the subset independence axiom requires a modification of the Lagrange multipliers one begins with thereby rendering the optimization less trustworthy. We also explicitly demonstrate that the Rényi entropy violates the subset independence axiom and compare it with the Shannon entropy. Thirdly, the new composition rule offered by Jizba and Korbel are shown to yield probability distributions even without a need for the entropy maximization procedure at the expense of creating artificial bias in the data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
