smoothScatter produces a smoothed color density
  representation of a scatterplot, obtained through a (2D) kernel
  density estimate.smoothScatter(x, y = NULL, nbin = 128, bandwidth,
              colramp = colorRampPalette(c("white", blues9)),
              nrpoints = 100, ret.selection = FALSE,
              pch = ".", cex = 1, col = "black",
              transformation = function(x) x^.25,
              postPlotHook = box,
              xlab = NULL, ylab = NULL, xlim, ylim,
              xaxs = par("xaxs"), yaxs = par("yaxs"), ...)x and y arguments provide the x and y
    coordinates for the plot.  Any reasonable way of defining the
    coordinates is acceptable.  See the function xy.coords
    for details.  If supplied separately, they must be of the same length.gridsize in bkde2D().bandwidth
    is subsequently passed to function
    bkde2D.n as an argument and
    returning n colors.nrpoints points from those areas of lowest
    regional densities will be plotted.  Adding points to the plot
    allows for the identification of outliers.  If all points are to be
    plotted, choose nrpoints = Inf.logical indicating to return the
    ordered indices of “low density” points if nrpoints > 0.NULL or a function which will be
    called (with no arguments) after image.image.image,
    e.g., add=TRUE or useRaster=TRUE.ret.selection is true, a vector of integers of length
  nrpoints (or smaller, if there are less finite points inside
  xlim and ylim) with the indices of the low-density
  points drawn, ordered with lowest density first.smoothScatter produces a smoothed version of a scatter plot.
  Two dimensional (kernel density) smoothing is performed by
  bkde2D from package https://CRAN.R-project.org/package=KernSmooth.
  See the examples for how to use this function together with
  pairs.bkde2D from package https://CRAN.R-project.org/package=KernSmooth;
  densCols which uses the same smoothing computations and
  blues9 in package grDevices. scatter.smooth adds a loess
  regression smoother to a scatter plot.