The paper starts with a presentation of some fundamental concepts of statistical information theory: a priori knowledge, a posteriori knowledge and probability. From this a systematic framework of assumptions related to the applicability of information theory concepts is established. This framework can be applied everywhere information measures are used as improbability indicators of nominal distributions, such as in trip distribution modelling.
Abstract