R/CRITIC.R

In RMCDA: Multi-Criteria Decision Analysis

#' Apply CRITIC on comparison matrix
#'
#' @param A the matrix A with row names corresponding to alternatives and column
#' names corresponding to criteria
#' @return the weight percentages related to matrix A obtained through the CRITIC method
#'
#' @examples
#' A <- matrix(c(250, 200, 300, 275,
#'  225, 16, 16, 32,
#'   32, 16, 12, 8,
#'    16, 8, 16, 5,
#'     3, 4, 4, 2), nrow=5, ncol=4)
#' colnames(A)<-c("Price", "Storage space", "Camera", "Looks")
#' rownames(A)<-paste0("Mobile ", seq(1, 5, 1))
#' A[,"Price"] <- -A[,"Price"]
#' apply.CRITIC(A)
#' @importFrom stats sd cor
#' @export apply.CRITIC
apply.CRITIC <- function(A){


  normalized.A <- apply(A, 2, function(x) (x - min(x))/(max(x)-min(x)))

  sigma.A <- apply(normalized.A, 2, sd)

  corr.A <- cor(normalized.A)

  measure.conflict <- rowSums(1-corr.A)

  weight.percentage <- measure.conflict*sigma.A/sum(measure.conflict*sigma.A)

  return(weight.percentage)

}