This function computes the probabilities of each alternative maximizing the preference per criterion, using Beta PERT distributions to randomize the decision matrix.
Decision matrix of Alternatives (rows) and Criteria (columns). Benefit criteria must be positive and cost criteria must be negative.
Shape of a Beta PERT distribution, as described in the package 'mc2d'. There is no default value, however the higher the shape the higher the kurtosis, which emulates the precision of data.
PMax are the joint probabilities of each alternative being higher than the others, per criterion.
Sant'Anna, Annibal P. (2015). Probabilistic Composition of Preferences: Theory and Applications, Springer.
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