推论多样性：香农之后的生活
Inferring Diversity: Life After Shannon
摘要：
一个社区的多样性不能完全统计，必须推断出来。两种最优秀的推理方法是MaxEnt方法和贝叶斯规则，MaxEnt方法使用约束形式的信息，贝叶斯规则使用数据形式的信息。结果表明，这两种方法都是最大（相对）熵（ME）方法的特例。我们演示了如何使用这种方法可以作为一种多样性的措施，不仅再现香农指数的功能，但超过他们允许更多类型的信息被包括在推理。并对一个具体的算例进行了详细的求解。此外，所发现的熵与热力学熵的形式相同。
英文摘要：
The diversity of a community that cannot be fully counted must be inferred. The two preeminent inference methods are the MaxEnt method, which uses information in the form of constraints and Bayes' rule which uses information in the form of data. It has been shown that these two methods are special cases of the method of Maximum (relative) Entropy (ME). We demonstrate how this method can be used as a measure of diversity that not only reproduces the features of Shannon's index but exceeds them by allowing more types of information to be included in the inference. A specific example is solved in detail. Additionally, the entropy that is found is the same form as the thermodynamic entropy.
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