Probabilities of judgments provided by unknown experts by using the imprecise Dirichlet model

Most models of aggregating expert judgments assume that there is available some information characterizing the experts. This information may be incorporated into the so-called hierarchical uncertainty models (second-order models). However, we often do not know anything about experts or it is difficult to evaluate their quality. In this case, beliefs to experts may be in the interval [0, 1] and the resulting assessments become to be non-informative. Moreover, attempts to assign some weights or beliefs to experts were not crowned with success because the behavior of experts may be distinguished in different circumstances. Therefore, this paper proposes to estimate expert judgm ents instead of experts themselves and studies how to assign interval probabilities of expert judgments by using a set of multinomial models.