Bayesian Elicitation Diagnostics
提出两种诊断方法，分别识别过于分散或集中于零的先验分布，若成立则无需更精确的先验启发，对计量经济学和贝叶斯统计学者有用。
One elicitation diagnostic identifies a family of prior distributions that are so diffuse that they are practically equivalent to the completely diffuse prior. Another elicitation diagnostic identifies a family of prior distributions that concentrate enough mass in the neighborhood of zero that they are practically equivalent to the dogmatic prior that sets a parameter exactly equal to zero. If either question thus posed can be answered in the affirmative then there is no need to go to the expense of a more accurate elicitation of the prior distribution. Copyright 1992 by The Econometric Society.