RMCriteria (version 0.2.0)

RPrometheeIVKernel: RPrometheeIVKernel

Description

The PROMETHEE IV KERNEL method was developed by Albuquerque and Montenegro (2015), as an alternative method to estimate PROMETHEE IV. It considers the empirical distribution of the criteria through kernel density estimation to evaluate alternatives.

Usage

RPrometheeIVKernel(RPrometheeArguments)

Arguments

RPrometheeArguments

An object with all RPromethee arguments. For PROMETHEE IV KERNEL, the object must be supplied with a band argument, for Kernel Density Estimation. See RPrometheeConstructor for more information.

Value

• PhiPlus The resulting PhiPlus from the alternatives for all criterias.

• PhiMinus The resulting PhiMinus from the alternatives for all criterias

• Index The resulting Index from the alternatives for all criterias

• alternatives The alternatives names.

• criterias The criterias names.

• datMat The data used corresponding to criterias and alternatives.

References

• P. H. M., Albuquerque, M. R. Montenegro. PROMETHEE IV through kernel density estimation Communications in Statistics - Theory and Methods v. 45, p.5355-5362, 2016. https://www.tandfonline.com/doi/full/10.1080/03610926.2014.942432

• M. Behzadian et al. PROMETHEE: A comprehensive literature review on methodologies and applications European Journal of Operational Research v. 200, p.198-215, 2010. https://www.sciencedirect.com/science/article/abs/pii/S0377221709000071

• J. P. Brans, Ph. Vincke A Preference Ranking Organisation Method: (The PROMETHEE Method for Multiple Criteria Decision-Making) Management science, v. 31, n. 6, p. 647-656, 1985. https://pdfs.semanticscholar.org/edd6/f5ae9c1bfb2fdd5c9a5d66e56bdb22770460.pdf

• J. P. Brans, B. Mareschal PROMETHEE methods. In: Figueria J, Greco S, Ehrgott M (eds) Multiple criteria decision analysis: state of the art surveys. Springer Science, Business Media Inc., Boston pp 163???195. http://www.springer.com/la/book/9780387230818

See Also

Other RPromethee methods: PrometheeIIIPlot, PrometheeIIPlot, PrometheeIPlot, PrometheeIVPlot, RPrometheeConstructor, RPrometheeIII, RPrometheeII, RPrometheeIV, RPrometheeI, RPrometheeV, SensitivityAnalysis, UpdateRPrometheeAlternatives, UpdateRPrometheeArguments, WalkingWeightsPlot, plot,RPrometheeI-method

Examples

# NOT RUN {
## Create objects for each argument
data <- matrix(c(5.2, -3.5,
                 4.3, -1.2,
                 6.7, -2.0,
                 5.4, -5.0,
                 4.8,  0.0,
                 2.8, -3.4), byrow = TRUE, ncol = 2)

parms <- matrix(c(1.0, 5.0), byrow = TRUE, ncol = 1, nrow = 2)
vecWeights <- c(0.3, 0.7)
vecMaximiz <- c(FALSE, TRUE)
prefFunction <- c(0, 0)
band <- as.matrix(apply(data, 2, bw.nrd0))
normalize <- FALSE
alternatives <- c("Alt 1", "Alt 2", "Alt 3")

## Create RPrometheeArguments object
PromObj <- RPrometheeConstructor(datMat = data, vecWeights = vecWeights,
vecMaximiz = vecMaximiz, prefFunction = prefFunction, parms = parms,
normalize = normalize, alternatives = alternatives, band = band)

## Run RPrometheeIVKernel
result <- RPrometheeIVKernel(PromObj)

## Updating alternatives name using UpdateRPrometheeAlternatives
newAlternatives <- c("A", "B", "C", "D", "E", "F")
result <- UpdateRPrometheeAlternatives(result, newAlternatives)

## Updating any argument using UpdateRPrometheeArguments
newParms <- matrix(c(1.6, 4.2), byrow = TRUE, ncol = 1)
PromObj <- UpdateRPrometheeArguments(PromObj, "parms", newParms)
result <- RPrometheeIVKernel(PromObj)
# }