Reasoning From Data in the Mathematical Theory of Evidence
  Mathematical Theory of Evidence (MTE) is known as a foundation for reasoning
when knowledge is expressed at various levels of detail. Though much research
effort has been committed to this theory since its foundation, many questions
remain open. One of the most important open questions seems to be the
relationship between frequencies and the Mathematical Theory of Evidence. The
theory is blamed to leave frequencies outside (or aside of) its framework. The
seriousness of this accusation is obvious: no experiment may be run to compare
the performance of MTE-based models of real world processes against real world
data.
  In this paper we develop a frequentist model of the MTE bringing to fall the
above argument against MTE. We describe, how to interpret data in terms of MTE
belief functions, how to reason from data about conditional belief functions,
how to generate a random sample out of a MTE model, how to derive MTE model
from data and how to compare results of reasoning in MTE model and reasoning
from data.
  It is claimed in this paper that MTE is suitable to model some types of
destructive processes
