Using of Non-Numeric, Non-Exact and Non-Complete Information for Alternatives’ Probabilities Estimation

A method of alternatives’ probabilities estimation under deficiency of numeric information (obtained from different sources) is proposed. The method is based on the well known Bayesian model of uncertainty randomization. Additional non-numeric, non-exact, and non-complete information about the sources’ significance are used for final estimation of the alternatives’ probabilities. Some examples of the method application to commodities’ prices and currencies rates dynamics forecasting are presented.