Using Dempster-Shafer Theory of Evidence, also called “Theory of Belief Functions”. Basic probability assignments, or mass functions, can be defined on the subsets of a set of possible values. Two mass functions can be combined using Dempster’s rule of combination. A mass function can be extended to a larger frame. Marginalization, i.e. reduction to a smaller frame can also be done. These features can be combined to analyze small belief networks and take into account situations where information cannot be satisfactorily described by probability distributions. # Installation Install from CRAN: install.package(“dst”) # Examples See the vignette: Monty-hall-Example.