INFINITESIMAL SENSITIVITY OF POSTERIOR DISTRIBUTIONS

We measure the local sensitivity of a posterior expectation with respect to the prior by computing the norm of the Frechet derivative of the posterior with respect to the prior over several different classes of measures. We compute the derivative of the posterior upper expectation when the prior varies in a restricted epsilon-contamination class. A bound on the global sensitivity of a class of priors is obtained. As an application, we show that of all sets with posterior probability 1-alpha, the likelihood region minimizes the norm of the Frechet derivative over the epsilon-contamination class and so is, in some sense, the most robust region with this posterior probability. But there exist counterexamples to this result for other classes of priors.