摘要
In Bayesian analysis, the maximum entropy prior is commonly used. But in some cases, the maximum entropy prior does not exist or has unpleasant jumps, In this paper, Fisher-information is used to measure the divergence and to derive the unknown prior. To a certain degree, this measure overcomes the shortcomings of the maximum entropy. The Fisher prior aways exists and it is continuous under the general requirements.
