# CPP.SAW.Entropy: CPP by weighted sum, with weights computed from Shannon... In CPP: Composition of Probabilistic Preferences (CPP)

## Description

This function computes the CPP-SAW, using Normal distributions to randomize the decision matrix and weights defined by entropy. The CPP-SAW Entropy is used to evaluate alternatives by weighted sum.

## Usage

 `1` ```CPP.SAW.Entropy(x) ```

## Arguments

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

## Value

Weights by entropy.PMax are the joint probabilities of each alternative being higher than the others, per criterion. CPP returns the alternatives' scores by weighted sum, indicating the preference ranks for decisionmaking.

## References

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

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```## 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) Alt.6 = c(6,29,79,-9) Alt.7 = c(8,37,55,-15) Alt.8 = c(10,21,69,-11) x = rbind(Alt.1,Alt.2,Alt.3,Alt.4,Alt.5,Alt.6,Alt.7,Alt.8) CPP.SAW.Entropy(x) ```

CPP documentation built on May 2, 2019, 1:34 p.m.