R/TSD.R

In NNS: Nonlinear Nonparametric Statistics

#' NNS TSD Test
#'
#' Bi-directional test of third degree stochastic dominance using lower partial moments.
#'
#' @param x a numeric vector.
#' @param y a numeric vector.
#' @param plot logical; \code{TRUE} (default) plots the TSD test.
#' @return Returns one of the following TSD results: \code{"X TSD Y"}, \code{"Y TSD X"}, or \code{"NO TSD EXISTS"}.
#' @author Fred Viole, OVVO Financial Systems
#' @references Viole, F. and Nawrocki, D. (2016) "LPM Density Functions for the Computation of the SD Efficient Set." Journal of Mathematical Finance, 6, 105-126.  \doi{10.4236/jmf.2016.61012}.
#' @examples
#' \dontrun{
#' set.seed(123)
#' x <- rnorm(100) ; y <- rnorm(100)
#' NNS.TSD(x, y)
#' }
#' @export

NNS.TSD <- function(x, y, plot = TRUE){

  to_numeric_vector <- function(v, arg_name){
    if(any(class(v)%in%c("tbl","data.table")) || is.data.frame(v) || is.matrix(v) || any(class(v) %in% c("xts", "zoo"))){
      if(!is.null(dim(v)) && ncol(v) > 1){
        stop(sprintf("%s must be a single-column object or numeric vector.", arg_name))
      }
      v <- as.vector(unlist(v, use.names = FALSE))
    }
    
    as.numeric(v)
  }
  
  x <- to_numeric_vector(x, "x")
  y <- to_numeric_vector(y, "y")
    
  if(anyNA(cbind(x,y))) stop("You have some missing values, please address.")

  Combined_sort <- sort(c(x, y), decreasing = FALSE)

  LPM_x_sort <- LPM(2, Combined_sort, x)
  LPM_y_sort <- LPM(2, Combined_sort, y)
    
  x.tsd.y <- any(LPM_x_sort > LPM_y_sort)
  y.tsd.x <- any(LPM_y_sort > LPM_x_sort)


  if(plot){
    plot(LPM_x_sort, type = "l", lwd = 3, col = "red", main = "TSD", ylab = "Area of Cumulative Distribution",
         ylim = c(min(c(LPM_y_sort, LPM_x_sort)), max(c(LPM_y_sort, LPM_x_sort))))

    lines(LPM_y_sort, type = "l", lwd =3,col = "steelblue")
    legend("topleft", c("X","Y"), lwd = 10, col=c("red","steelblue"))
  }
    
  ifelse (!x.tsd.y && min(x) >= min(y) && mean(x) >= mean(y) && !identical(LPM_x_sort, LPM_y_sort),
          "X TSD Y",
          ifelse (!y.tsd.x && min(y) >= min(x) && mean(y) >= mean(x) && !identical(LPM_x_sort, LPM_y_sort),
                  "Y TSD X",
                  "NO TSD EXISTS"))

}