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RMCriteria is a package to solve Multiple-Criteria Decision Analysis (MCDA) problems. For now, it only supports Promethee methods, but other methods may be developed in the future.

Home Page: http://lamfo.unb.br/

C++ 33.20% R 66.80%

multicriteria-decision-analysis promethee decision-making mcda

rmcriteria's Introduction

RMCriteria

Overview

RMCriteria is a package to solve Multiple-Criteria Decision Analysis (MCDA) problems. For now, it only supports Promethee methods, but other methods may be developed in the future.

Installation

Currently, the easiest way to install RMCriteria is through devtools package, straight from GitHub:

# install.packages("devtools")
devtools::install_github("lamfo-unb/RMCriteria")

Usage

Using RMCriteria is quite simple. The general idea is to create a RPrometheeArguments object, with all parameters such as the criterias and alternatives and then applying this object to the chosen method, like RPrometheeI.

## Create objects for each argument
data <-matrix(c(5.2,-3.5,
                4.3,-1.2,
                6.7,-2.0), byrow = T, ncol=2, nrow=3)

parms <- matrix(c(NA,
                NA),byrow=TRUE,ncol=1,nrow=2)

vecWeights <- c(0.3,0.7)
vecMaximiz <- c(F,T)
prefFunction <- c(0,0)
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)

# Run RPrometheeI
(result <- RPrometheeI(PromObj))

More Information

RMCriteria was developed in the Laboratory of Machine Learning in Finance and Organizations (LAMFO) from University of Brasilia, in Brazil. LAMFO is a center devoted to research machine learning methods and related subjects applied to organizations in Marketing, Finance, Logistics and many others.

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rmcriteria's Issues

Edit README with package information

Adjust RPrometheeV S4 classes

Adjust RPrometheeV class to include lp class from lpSolve package.

Create the S4 class for the PrometheeI Rcpp function.

Create the S4 class for the PrometheeI Rcpp function.

Create the manual for the PrometheeIII S4 method.

Create the manual for the PrometheeIII S4 method.

Create the manual for the PrometheeI S4 method.

Create the manual for the PrometheeI S4 method.

Create print function and its manual

Create the manual for the PrometheeII S4 method.

Create the manual for the PrometheeII S4 method.

Add reference for PrometheeV manual

Create the manual for the SensitivityAnalysis S4 method.

Create the manual for the SensitivityAnalysis S4 method.

Create the S4 class for the PrometheeIII Rcpp function.

Create the S4 class for the PrometheeIII Rcpp function.

Create the Standard functions manual.

Create the Standard functions manual.

Create the manual for the PrometheeV S4 method.

Create the manual for the PrometheeV S4 method.

Create the Promethee Network.

Create the Promethee Network plot based on Gaia/Promethee,

Create the S4 class for the PrometheeV Rcpp function.

Create the S4 class for the PrometheeV Rcpp function.

Create the manual for the PrometheeIV and PrometheeIVKernel S4 method.

Create the manual for the PrometheeIV and PrometheeIVKernel S4 method.

Create the S4 class for the PrometheeII Rcpp function.

Create the S4 class for the PrometheeII Rcpp function.

Create the Promethee Ranking plot.

Create the Promethee Ranking plot based on Gaia/Promethee,

Create the Walking Weights plot.

Create the Walking Weights plot.

Create the S4 class for the SensitivityAnalysis code.

Create the S4 class for the SensitivityAnalysis code in the R folder.

Create "pause" for global plot function

Create the S4 class for the PrometheeIV and PrometheeIVKernel Rcpp function.

Create the S4 class for the PrometheeIV and PrometheeIVKernel Rcpp function.

Standard functions.

Create the R standard functions like print, summary, plot. An example: http://www.quantide.com/ramarro-chapter-07/

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