Exact and efficient inference for Partial Bayes problems

摘要: Bayesian methods are useful for statistical inference. However, real-world problems can be challenging using when the data analyst has only limited prior knowledge. In this paper we consider a class of problems, called Partial Bayes in which information is partially available. Taking recently proposed Inferential Model approach, develop general inference framework and derive both exact efficient solutions. addition to theoretical investigation, numerical results real applications used demonstrate superior performance method.