Package: MCDA 0.0.24

Patrick Meyer

MCDA: Support for the Multicriteria Decision Aiding Process

Support for the analyst in a Multicriteria Decision Aiding (MCDA) process with algorithms, preference elicitation and data visualisation functions. Sébastien Bigaret, Richard Hodgett, Patrick Meyer, Tatyana Mironova, Alexandru Olteanu (2017) Supporting the multi-criteria decision aiding process : R and the MCDA package, Euro Journal On Decision Processes, Volume 5, Issue 1 - 4, pages 169 - 194 <doi:10.1007/s40070-017-0064-1>.

Authors:Patrick Meyer, Sébastien Bigaret, Richard Hodgett, Alexandru-Liviu Olteanu

MCDA_0.0.24.tar.gz
MCDA_0.0.24.zip(r-4.5)MCDA_0.0.24.zip(r-4.4)MCDA_0.0.24.zip(r-4.3)
MCDA_0.0.24.tgz(r-4.4-any)MCDA_0.0.24.tgz(r-4.3-any)
MCDA_0.0.24.tar.gz(r-4.5-noble)MCDA_0.0.24.tar.gz(r-4.4-noble)
MCDA_0.0.24.tgz(r-4.4-emscripten)MCDA_0.0.24.tgz(r-4.3-emscripten)
MCDA.pdf |MCDA.html
MCDA/json (API)

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

Peer review:

Bug tracker:https://github.com/paterijk/mcda/issues

On CRAN:

6.01 score 28 stars 181 scripts 907 downloads 306 mentions 47 exports 36 dependencies

Last updated 2 years agofrom:ff40fd048c. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 23 2024
R-4.5-winOKNov 23 2024
R-4.5-linuxOKNov 23 2024
R-4.4-winOKNov 23 2024
R-4.4-macOKNov 23 2024
R-4.3-winOKNov 23 2024
R-4.3-macOKNov 23 2024

Exports:additiveValueFunctionElicitationAHPapplyPiecewiseLinearValueFunctionsOnPerformanceTableassignAlternativesToCategoriesByThresholdsELECTRE3ELECTREIIIDistillationLPDMRSortLPDMRSortIdentifyIncompatibleAssignmentsLPDMRSortIdentifyUsedDictatorProfilesLPDMRSortIdentifyUsedVetoProfilesLPDMRSortInferenceApproxLPDMRSortInferenceExactMAREMRSortMRSortIdentifyIncompatibleAssignmentsMRSortIdentifyUsedVetoProfilesMRSortInferenceApproxMRSortInferenceExactMRSortIntervalnormalizePerformanceTablepairwiseConsistencyMeasuresplotAlternativesValuesPreorderplotMAREplotMRSortSortingProblemplotPiecewiseLinearValueFunctionsplotRadarPerformanceTableplotSUREPROMETHEEIPROMETHEEIIPROMETHEEOutrankingFlowsPROMETHEEPreferenceIndicesSRMPSRMPInferenceSRMPInferenceApproxSRMPInferenceApproxFixedLexicographicOrderSRMPInferenceApproxFixedProfilesNumberSRMPInferenceFixedLexicographicOrderSRMPInferenceFixedProfilesNumberSRMPInferenceNoInconsistSRMPInferenceNoInconsistFixedLexicographicOrderSRMPInferenceNoInconsistFixedProfilesNumberSURETOPSISUTAUTADISUTASTARweightedSum

Dependencies:assertthatclicolorspacecombinatfansifarverggplot2glpkAPIgluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppRglpkrlangscalesslamtibbletriangleutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Elicitation of a general additive value function.additiveValueFunctionElicitation
Analytic Hierarchy Process (AHP) methodAHP
Applies value functions on a performance table.applyPiecewiseLinearValueFunctionsOnPerformanceTable
Assign alternatives to categories according to thresholds.assignAlternativesToCategoriesByThresholds
ELimination Et Choice Translating REality - ELECTRE-IIIELECTRE3
ELECTRE III rankingELECTREIIIDistillation
MRSort that takes into account large performance differences.LPDMRSort
Identifies all sets of assignment examples which are incompatible with the MRSort sorting method extended to handle large performance differences.LPDMRSortIdentifyIncompatibleAssignments
Identify dictator profiles evaluations that have an impact on the final assignments of MRSort with large performance differencesLPDMRSortIdentifyUsedDictatorProfiles
Identify veto profiles evaluations that have an impact on the final assignments of MRSort with large performance differencesLPDMRSortIdentifyUsedVetoProfiles
Identification of profiles, weights, majority threshold, veto and dictator thresholds for LPDMRSort using a genetic algorithm.LPDMRSortInferenceApprox
Identification of profiles, weights, majority threshold and veto and dictator thresholds for the MRSort sorting approach extended to handle large performance differences.LPDMRSortInferenceExact
Multi-Attribute Range Evaluations (MARE)MARE
Electre TRI-like sorting method axiomatized by Bouyssou and Marchant.MRSort
Identifies all sets of assignment examples which are incompatible with the MRSort method.MRSortIdentifyIncompatibleAssignments
Identify veto profiles evaluations that have an impact on the final assignments of MRSortMRSortIdentifyUsedVetoProfiles
Identification of profiles, weights, majority threshold and veto thresholds for MRSort using a genetic algorithm.MRSortInferenceApprox
Identification of profiles, weights and majority threshold for the MRSort sorting method using an exact approach.MRSortInferenceExact
MRSort with imprecise evaluationsMRSortInterval
Function to normalize (or rescale) the columns (or criteria) of a performance table.normalizePerformanceTable
Consistency Measures for Pairwise Comparison MatricespairwiseConsistencyMeasures
Function to plot a preorder of alternatives, based on some score or ranking.plotAlternativesValuesPreorder
Plot Multi-Attribute Range Evaluations (MARE)plotMARE
Plot the categories and assignments of an Electre TRI-like sorting problem (via separation profiles).plotMRSortSortingProblem
Function to plot piecewise linear value functions.plotPiecewiseLinearValueFunctions
Function to plot radar plots of alternatives of a performance table.plotRadarPerformanceTable
Plot SURE kernel density plots.plotSURE
PROMETHEE IPROMETHEEI
PROMETHEE IIPROMETHEEII
Outranking flows for the PROMETHEE methodsPROMETHEEOutrankingFlows
Preference indices for the PROMETHEE methodsPROMETHEEPreferenceIndices
SRMP: a simple ranking method using reference profilesSRMP
Exact inference of an SRMP model given a maximum number of reference profilesSRMPInference
Approximative inference of an SRMP modelSRMPInferenceApprox
Approximative inference of an SRMP model given the lexicographic order of the profilesSRMPInferenceApproxFixedLexicographicOrder
Approximative inference of an SRMP model given the number of reference profilesSRMPInferenceApproxFixedProfilesNumber
Exact inference of an SRMP model given the lexicographic order of the profilesSRMPInferenceFixedLexicographicOrder
Exact inference of an SRMP model given the number of reference profilesSRMPInferenceFixedProfilesNumber
Exact inference of an SRMP model given a maximum number of reference profiles - no inconsistenciesSRMPInferenceNoInconsist
Exact inference of an SRMP model given the lexicographic order of the profiles - no inconsistenciesSRMPInferenceNoInconsistFixedLexicographicOrder
Exact inference of an SRMP model given the number of reference profiles - no inconsistenciesSRMPInferenceNoInconsistFixedProfilesNumber
Simulated Uncertainty Range Evaluations (SURE)SURE
Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodTOPSIS
UTA method to elicit value functions.UTA
UTADIS method to elicit value functions in view of sorting alternatives in ordered categoriesUTADIS
UTASTAR method to elicit value functions.UTASTAR
Weighted sum of evaluations of alternatives.weightedSum