Data-dependent probability matching priors of the second order

摘要

We consider second-order probability matching priors that ensure frequentist validity of posterior quantiles with margin of error o(n~(-1)), where n is the sample size. It is well known that there are many models of interest where data-free second-order probability matching priors do not exist. We explore how this problem can be resolved via consideration of data-dependent priors. This is done both in the absence and presence of nuisance parameters.