R/mNearestN.R

In RozetaSimonovska/SDPDmod: Spatial Dynamic Panel Data Modeling

#' @name mNearestN
#'
#' @title m nearest neighbors based on a distance matrix
#'
#' @description This function finds the m nearest neighbors, given a matrix of distances.
#'
#' @param distMat distance matrix
#' @param m number of nearest neighbors, default value 5
#' @param listv logical, default FALSE. If TRUE the list of neighbors should also be returned
#' @param rn logical, default FALSE. If TRUE, the spatial weights matrix will be row-normalized
#'
#' @return
#' \item{W}{spatial weights matrix }
#' \item{nlist}{list of indexes of the m nearest neighbors}
#'
#' @author Rozeta Simonovska
#'
#' @examples
#' data(gN3dist, package = "SDPDmod")
#' fournn <- mNearestN(gN3dist, m = 4)
#' mat1   <- rownor(fournn)
#' tennn  <- mNearestN(gN3dist, 10, listv = TRUE, rn = TRUE)
#' mat2   <- tennn$W
#'
#' @export


mNearestN<-function(distMat, m = 5,listv = FALSE, rn = FALSE){

  if(isSymmetric(distMat) & all(diag(distMat)==0)){
    n<-nrow(distMat)
    list_ngb<-vector("list",n)

    for(i in 1:n){
      ordRow<-order(distMat[i,], decreasing = FALSE)
      nRow<-ordRow[which(ordRow!=i)]
      if(length(nRow)>=m){
        list_ngb[[i]]<-nRow[1:m]
      } else {
        list_ngb[[i]]<-nRow[1:n]
        warning("m is larger than total number of individuals/regions")
      }
    }
  } else { stop("Error in distMat! Not a distance matrix.")}

  W<-matrix(0,nrow=n,ncol=n)
  for(i in 1:n){  W[i,list_ngb[[i]]]<-1  }
  if(rn){ W <- rownor(W) }

  if(listv){
    return(list(W = W, nlist = list_ngb))
  }else{
      return(W) }
}