Towards a geometry of imprecise inference

If the base measure is considered a prior distribution, then the translation by the observed log-likelihood defines the posterior. An imprecise prior defined by a set of measures is in the same manner translated to a set of posterior measures. Upper and lower previsions can then be computed as extrema over this posterior set.