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ConsRank (version 1.0.1)

ConsRank-package: Compute the Median Ranking(s) According to the Kemeny's Axiomatic Approach

Description

Compute the median ranking according the Kemeny's axiomatic approach. Rankings can or cannot contain ties, rankings can be both complete or incomplete.

Arguments

Details

ll{ Package: ConsRank Type: Package Version: 1.0.1 Date: 2015-09-01 License: GPL-3 }

References

Kemeny, J. G., & Snell, J. L. (1962). Mathematical models in the social sciences (Vol. 9). New York: Ginn. Marden, J. I. (1996). Analyzing and modeling rank data. CRC Press. Emond, E. J., & 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. Heiser, W. J., & D'Ambrosio, A. (2013). Clustering and prediction of rankings within a Kemeny distance framework. In Algorithms from and for Nature and Life (pp. 19-31). Springer International Publishing. Amodio, S., D'Ambrosio, A. & Siciliano, R (2015). Accurate algorithms for identifying the median ranking when dealing with weak and partial rankings under the Kemeny axiomatic approach. European Journal of Operational Research. DOI: 10.1016/j.ejor.2015.08.048. D'Ambrosio, A., Amodio, S. & Iorio, C. (2015). Two algorithms for finding optimal solutions of the Kemeny rank aggregation problem for full rankings. Technical report, University of Naples Federico II. Submitted.

Examples

Run this code
## load APA data set, full version
data(APAFULL)
## Emond and Mason Branch-and-Bound algorithm. 
## If the number of object is higher than 20, EMCons function may work for several minutes. 
## Use either QuickCons or FASTcons instead
CR=EMCons(APAFULL)
TR=tabulaterows(APAFULL)
CR2=FASTcons(TR$X,TR$Wk,maxiter=5)
CR3=QuickCons(TR$X,TR$Wk)

#####################################
### load sports data set
#data(sports)
### FAST algorithm
#CR=FASTcons(sports,maxiter=10)
#####################################

#######################################
### load Emond and Mason data set
#data(EMD)
### matrix X contains rankings
#X=EMD[,1:15]
### vector Wk contains frequencies
#Wk=EMD[,16]
### QUICK algorithm
#CR=QuickCons(X,Wk)
#######################################

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