PMax.Beta {CPP}

Probabilities of maximization, by Beta PERT distributions

Description

This function computes the probabilities of each alternative maximizing the preference per criterion, using Beta PERT distributions to randomize the decision matrix.

Usage

PMax.Beta(x, s)

Arguments

x

Decision matrix of Alternatives (rows) and Criteria (columns). Benefit criteria must be positive and cost criteria must be negative.

s

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.

Value

PMax are the joint probabilities of each alternative being higher than the others, per criterion.

References

Sant'Anna, Annibal P. (2015). Probabilistic Composition of Preferences: Theory and Applications, Springer.

Examples

# Decision matrix
Alt.1 = c(2,30,86,-5)
Alt.2 = c(4,26,77,-12)
Alt.3 = c(3,22,93,-4)
Alt.4 = c(6,34,65,-10)
Alt.5 = c(5,31,80,-8)
x = rbind(Alt.1,Alt.2,Alt.3,Alt.4,Alt.5)
s = 4 # Shape
PMax.Beta(x,s)