R/MAVF_scores.R

In AFIT-R/MODA: Implementation of Multi Objective Decision Analysis

#'@title Multiple Attribute Value Function (MAVF) Scores
#' 
#'@description: Takes a matrix of Single Attribute Value Functions (SAVF) scores and multiplies it by the weights vector to calculate the 
#'alternatives MAVF score.
#'
#'@param SAVF_matrix Matrix of SAVF scores
#'@param weights Numeric vector of SAVF weights
#'@param names Vector of attribute names
#'
#'@return MAVF Scores
#'
#'@examples
#'\dontrun{ 
#'
#'qbdata <- NFLcombine[1:7,]
#'
#'Height <- SAVF_exp_score(qbdata$heightinchestotal, 68, 75.21, 82)
#'Weight <- SAVF_exp_score(qbdata$weight, 185, 224.34, 275)
#'Forty <- SAVF_exp_score(qbdata$fortyyd, 4.3, 4.81, 5.4, increasing=FALSE)
#'Shuttle <- SAVF_exp_score(qbdata$twentyss, 3.8, 4.3, 4.9, increasing=FALSE)
#'Vertical <- SAVF_exp_score(qbdata$vertical, 21, 32.04, 40)
#'Broad <- SAVF_exp_score(qbdata$broad, 90, 111.24, 130)
#'Wonderlic <- SAVF_exp_score(qbdata$wonderlic, 0, 27.08, 50)
#'
#'SAVF_matrix = cbind(Height, Weight, Forty, Shuttle, 
#'                   Vertical, Broad, Wonderlic)
#'weights = c(0.096, 0.224, 0.092, 0.138, 0.152, 0.228, 0.07)
#'
#'MAVF_Scores(SAVF_matrix, weights, qbdata$name)}
#'
#'
#' @export

MAVF_Scores <- function(SAVF_matrix, weights, names){
  
  if(class(SAVF_matrix) != "matrix") {
    stop('SAVF_matrix must be a matrix\n',
         'You have provided an object of the following class:\n', 
         'SAVF_matrix: ', class(SAVF_matrix), '\n')
  }
  
  if(class(weights) != "matrix"){
    
    if(class(weights) != "numeric") {
      stop('weights must be of class numeric\n',
           'You have provided an object of the following class:\n', 
           'weights: ', class(weights))
    }
    if(sum(weights)< 1) {
      warning('The sum of weights is less than 1')
    }
    
    if(sum(weights)> 1) {
      warning('The sum of weights is greater than 1')
    }
    
    if(ncol(SAVF_matrix) != length(weights)) {
      stop('The number of columns in the SAVF matrix must equal the length of the vector of weights')
    }
    
    if(nrow(SAVF_matrix) != length(names) ) {
      stop('The number of rows in the SAVF matrix must equal the length of the vector of names')
    }
  }
  
  SAVF_matrix[is.na(SAVF_matrix)] <- 0
  

  MAVF = SAVF_matrix %*% weights
  value <- data.frame(names, MAVF)
  names(value) <- c("Name", "Score")
  value <- value[order(value$Score, decreasing = TRUE),]
  return(value)
}