EMCons {ConsRank} R Documentation

## Branch-and-bound algorithm to find consensus (median) ranking according to the Kemeny's axiomatic approach

### Description

Branch-and-bound algorithm to find consensus ranking as definned by Emond and Mason (2002). If the number of objects to be ranked is large (greater than 15 or 20, specially if there are missing rankings), it can work for very long time.

### Usage

EMCons(X, Wk = NULL, PS = TRUE)


### Arguments

 X A N by M data matrix, in which there are N judges and M objects to be judged. Each row is a ranking of the objects which are represented by the columns. Alternatively X can contain the rankings observed only once. In this case the argument Wk must be used Wk Optional: the frequency of each ranking in the data PS If PS=TRUE, on the screen some information about how many branches are processed are displayed

### Details

This function is deprecated and it will be removed in the next release of the package. Use function 'consrank' instead.

### Value

a "list" containing the following components:

 Consensus the Consensus Ranking Tau averaged TauX rank correlation coefficient Eltime Elapsed time in seconds

### Author(s)

Antonio D'Ambrosio antdambr@unina.it

### References

Emond, E. J., and Mason, D. W. (2002). A new rank correlation coefficient with application to the consensus ranking problem. Journal of Multi-Criteria Decision Analysis, 11(1), 17-28.

consrank

### Examples

data(Idea)
RevIdea=6-Idea
# as 5 means "most associated", it is necessary compute the reverse ranking of
# each rankings to have rank 1 = "most associated" and rank 5 = "least associated"
CR=EMCons(RevIdea)



[Package ConsRank version 2.1.4 Index]