Publication Date
7-2019
Abstract
To make an adequate decision, we need to know the probabilities of different consequences of different actions. In practice, we only have partial information about these probabilities -- this situation is known as imprecise probabilities. A general description of all possible imprecise probabilities requires using infinitely many parameters. In practice, the two most widely used few-parametric approximate descriptions are p-boxes (bounds on the values of the cumulative distribution function) and interval-valued moments (i.e., bounds on moments). In some situations, these approximations are not sufficiently accurate. So, we need more accurate more-parametric approximations. In this paper, we explain what are the natural next approximations.
Comments
Technical Report: UTEP-CS-19-78
To appear in V. Kreinovich (ed.), Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas, Springer, Cham, Switzerland.