R/getNormDS.R

In steepness: Testing Steepness of Dominance Hierarchies

# Function to obtain the normalized David's scores (NormDS) based on dyadic dominance indices #

getNormDS <- function(X,names=NULL,method=c("Dij","Pij")){
  if (nrow(X) != ncol(X)) 
    return("Error: Sociomatrix must be square");
  if ( sum(is.na(X))>0 || !is.numeric(X))
    return("Error: Sociomatrix must be numeric");
  method <- match.arg(method)
  dyadc <- X + t(X);
  if (method == "Dij"){
    Dij <- X/dyadc-(((X/dyadc)-0.5)/(dyadc+1))
    Dij[is.nan(Dij)] <- 0.
    w1 <- rowSums(Dij);
    w2 <- Dij%*%w1;
    l1 <-colSums(Dij);
    l2 <- t(l1)%*%Dij;
  }
  if (method == "Pij"){
    Pij <- array(dim=c(nrow(X),ncol(X)),0.);
    Pij <- X/dyadc;
    Pij[is.nan(Pij)] <- 0.
    w1 <- rowSums(Pij);
    w2 <- Pij%*%w1;
    l1 <-colSums(Pij);
    l2 <- t(l1)%*%Pij;
  }  
DS <- w1 + w2 - l1 - t(l2);
maxDS <- nrow(X)*(nrow(X)-1)/2;
NormDS <- (DS + maxDS)/nrow(X);
if (is.null(names)) names <- paste('Ind.',1:nrow(X))
NormDS <- array(NormDS,dim=c(nrow(X),1),dimnames=c(list(names),"NormDS"))
return(NormDS)
}