  An advantage of methods that base inference on a posterior distribution is
that credible regions are readily obtained. Except in well-specified
situations, however, there is no guarantee that such regions will achieve the
nominal frequentist coverage probability, even approximately. To overcome this
difficulty, we propose a general strategy that introduces an additional scalar
tuning parameter to control the posterior spread, and we develop an algorithm
that chooses this parameter so that the corresponding credible region achieves
the nominal coverage probability.
