Editing Principle of maximum entropy (section)

{{Short description|Principle in Bayesian statistics}}
{{other uses of|Maximum entropy}}
{{more footnotes|date=September 2008}}
{{Bayesian statistics}}

The '''principle of maximum entropy''' states that the [[probability distribution]] which best represents the current state of knowledge about a system is the one with largest [[Entropy (information theory)|entropy]], in the context of precisely stated prior data (such as a [[proposition]] that expresses [[#Testable information|testable information]]).

Another way of stating this:  Take precisely stated prior data or testable information about a probability distribution function. Consider the set of all trial probability distributions that would encode the prior data. According to this principle, the distribution with maximal [[information entropy]] is the best choice.