Description Usage Arguments Value Author(s) References See Also Examples
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.
1 |
RPrometheeArguments |
An object with all RPromethee arguments. For
PROMETHEE IV KERNEL, the object must be supplied with a |
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.
Pedro Henrique Melo Albuquerque, pedroa@unb.br
Gustavo Monteiro Pereira, monteirogustavop@gmail.com
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
Other RPromethee methods: PrometheeIIIPlot
,
PrometheeIIPlot
,
PrometheeIPlot
,
PrometheeIVPlot
,
RPrometheeConstructor
,
RPrometheeIII
, RPrometheeII
,
RPrometheeIV
, RPrometheeI
,
RPrometheeV
,
SensitivityAnalysis
,
UpdateRPrometheeAlternatives
,
UpdateRPrometheeArguments
,
WalkingWeightsPlot
,
plot,RPrometheeI-method
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | ## 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)
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