Package: ConsRank 2.1.4

Antonio DAmbrosio

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 declare as deprecated some functions that are still in the package for compatibility. Next release will not contains these functions. Please type '?ConsRank-deprecated' 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>.

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

ConsRank_2.1.4.tar.gz
ConsRank_2.1.4.tar.gz(r-4.5-noble)ConsRank_2.1.4.tar.gz(r-4.4-noble)
ConsRank_2.1.4.tgz(r-4.4-emscripten)ConsRank_2.1.4.tgz(r-4.3-emscripten)
ConsRank.pdf |ConsRank.html✨
ConsRank/json (API)

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

Peer review:

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
  • USAranks - USA rank data
  • sports - Sports data

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

27 exports 3 stars 2.35 score 49 dependencies 8 dependents 2 mentions 23 scripts 2.0k downloads

Last updated 8 months agofrom:c0f52082de. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 03 2024
R-4.5-linuxOKSep 03 2024

Exports:BBFULLcombinpmatrconsrankDECOREMConsFASTconsFASTDECORiw_kemenydiw_tau_xiwcombinpmatriwquickconskemenydkemenydesignkemenyscorelabelsorder2rankpartitionspolyplotQuickConsrank2orderreorderingscorematrixstirling2tabulaterowstau_xTau_Xunivranks

Dependencies:base64encbslibcachemclicpp11data.tabledigestdplyrevaluatefansifastmapfontawesomefsgenericsgluegtoolshighrhtmltoolshtmlwidgetsjquerylibjsonliteknitrlifecyclemagrittrmemoisemimepillarpkgconfigproxypurrrR6rappdirsrglrlangrlistrmarkdownsassstringistringrtibbletidyrtidyselecttinytexutf8vctrswithrxfunXMLyaml

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
Branch-and-Bound algorithm to find the median ranking in the space of full (or complete) rankings.BBFULL
Brook and Upton dataBU
Combined input matrix of a data setcombinpmatr
Branch-and-bound and heuristic algorithms to find consensus (median) ranking according to the Kemeny's axiomatic approachconsrank
Deprecated functions in ConsRankConsRank-deprecated
Differential Evolution algorithm for Median RankingDECOR
Branch-and-bound algorithm to find consensus (median) ranking according to the Kemeny's axiomatic approachEMCons
Emond and Mason dataEMD
FAST algorithm to find consensus (median) ranking. FAST algorithm to find consensus (median) ranking defined by Amodio, D'Ambrosio and Siciliano (2016). It returns at least one of the solutions. If there are multiple solutions, sometimes it returns all the solutions, sometimes it returns some solutions, always it returns at least one solution.FASTcons
FAST algorithm calling DECORFASTDECOR
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
Score matrix according Kemeny (1962)kemenyscore
Transform a ranking into a ordering.labels
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
Quick algorithm to find up to 4 solutions to the consensus ranking problemQuickCons
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