Package: ConsRank 3.0

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

Compute the median ranking according to the Kemeny's axiomatic approach. Rankings can or cannot contain ties, rankings can be both complete or incomplete. The package contains both branch-and-bound algorithms and heuristic solutions recently proposed. The searching space of the solution can either be restricted to the universe of the permutations or unrestricted to all possible ties. The package also provide some useful utilities for deal with preference rankings, including both element-weight Kemeny distance and correlation coefficient. This release includes also the median constrained bucket order algorithm. This release removes the functions previously declared as deprecated. These functions are now defunct and no longer available in the package. Essential references: Emond, E.J., and Mason, D.W. (2002) <doi:10.1002/mcda.313>; D'Ambrosio, A., Amodio, S., and Iorio, C. (2015) <doi:10.1285/i20705948v8n2p198>; Amodio, S., D'Ambrosio, A., and Siciliano R. (2016) <doi:10.1016/j.ejor.2015.08.048>; D'Ambrosio, A., Mazzeo, G., Iorio, C., and Siciliano, R. (2017) <doi:10.1016/j.cor.2017.01.017>; Albano, A., and Plaia, A. (2021) <doi:10.1285/i20705948v14n1p117>; D'Ambrosio, A., Iorio, C., Staiano, M. and Siciliano, R (2019) <doi:10.1007/s00180-018-0858-z>.

Authors:Antonio D'Ambrosio [aut, cre], Sonia Amodio [ctb], Giulio Mazzeo [ctb], Alessandro Albano [ctb], Antonella Plaia [ctb]

ConsRank_3.0.tar.gz
ConsRank_3.0.zip(r-4.7)ConsRank_3.0.zip(r-4.6)ConsRank_3.0.zip(r-4.5)
ConsRank_3.0.tgz(r-4.6-x86_64)ConsRank_3.0.tgz(r-4.6-arm64)ConsRank_3.0.tgz(r-4.5-x86_64)ConsRank_3.0.tgz(r-4.5-arm64)
ConsRank_3.0.tar.gz(r-4.7-arm64)ConsRank_3.0.tar.gz(r-4.7-x86_64)ConsRank_3.0.tar.gz(r-4.6-arm64)ConsRank_3.0.tar.gz(r-4.6-x86_64)
ConsRank_3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
ConsRank/json (API)

# Install 'ConsRank' in R:
install.packages('ConsRank', repos = c('https://antdambr.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/antdambr/consrank/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • APAFULL - American Psychological Association dataset, full version
  • APAred - American Psychological Association dataset, reduced version with only full rankings
  • BU - Brook and Upton data
  • EMD - Emond and Mason data
  • German - German political goals
  • Idea - Idea data set
  • sports - Sports data
  • USAranks - USA rank data

On CRAN:

Conda:

cpp

4.99 score 1 stars 10 packages 29 scripts 5.7k downloads 2 mentions 30 exports 28 dependencies

Last updated from:8fb00d54b3. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK166
linux-devel-x86_64OK194
source / vignettesOK214
linux-release-arm64OK203
linux-release-x86_64OK166
macos-release-arm64OK179
macos-release-x86_64OK292
macos-oldrel-arm64OK229
macos-oldrel-x86_64OK382
windows-develOK143
windows-releaseOK151
windows-oldrelOK176
wasm-releaseOK160

Exports:BBFULLcombinpmatrconsrankDECOREMConsFASTconsFASTDECORiw_kemenydiw_tau_xiwcombinpmatriwquickconskemenydkemenydesignkemenydesign_cppkemenyscorelabelsmcboorder2rankpartitionspolyplotpolyplotnewQuickConsrank2orderreorderingscorematrixstirling2tabulaterowstau_xTau_Xunivranks

Dependencies:clicpp11data.tabledplyrgenericsgluegtoolsjsonlitelifecyclemagrittrpillarpkgconfigproxypurrrR6Rcpprlangrliststringistringrtibbletidyrtidyselectutf8vctrswithrXMLyaml

Readme and manuals

Help Manual

Help pageTopics
Median Ranking Approach According to the Kemeny's Axiomatic ApproachConsRank-package ConsRank
American Psychological Association dataset, full versionAPAFULL
American Psychological Association dataset, reduced version with only full rankingsAPAred
Brook and Upton dataBU
Combined input matrix with C++ optimizationcombinpmatr
Branch-and-bound and heuristic algorithms to find consensus (median) ranking according to the Kemeny's axiomatic approachconsrank
Emond and Mason dataEMD
German political goalsGerman
Idea data setIdea
Item-weighted Kemeny distanceiw_kemenyd
Item-weighted TauX rank correlation coefficientiw_tau_x
Item-weighted Combined input matrix of a data setiwcombinpmatr
The item-weighted Quick algorithm to find up to 4 solutions to the consensus ranking problemiwquickcons
Kemeny distancekemenyd
Auxiliary functionkemenydesign
Kemeny design matrix (C++ implementation)kemenydesign_cpp
Score matrix according Kemeny (1962)kemenyscore
Median Constrained Bucket Order (MCBO)mcbo
Given an ordering, it is transformed to a rankingorder2rank
Generate partitions of n items constrained into k non empty subsetspartitions
Plot rankings on a permutation polytope of 3 o 4 objects containing all possible tiespolyplot
Plot rankings on a permutation polytope of 3 or 4 objectspolyplotnew
Given a rank, it is transformed to a orderingrank2order
Given a vector (or a matrix), returns an ordered vector (or a matrix with ordered vectors)reordering
Score matrix according Emond and Mason (2002)scorematrix
sports datasports
Stirling numbers of the second kindstirling2
Frequency distribution of a sample of rankingstabulaterows
TauX (tau exstension) rank correlation coefficientTau_X tau_x
Generate the universe of rankingsunivranks
USA rank dataUSAranks