smoothScatter produces a smoothed color density
representation of the scatterplot, obtained through a kernel
density estimate. densCols produces a vector containing
colors which encode the local densities at each point in a
scatterplot.
smoothScatter(x, y = NULL, nbin = 128, bandwidth, colramp = colorRampPalette(c("white", blues9)), nrpoints = 100, 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.NULL or a function which will be
called (with no arguments) after image.image.image.smoothScatter produces a smoothed version of a scatter plot.
Two dimensional (kernel density) smoothing is performed by
bkde2D from package \href{https://CRAN.R-project.org/package=#1}{\pkg{#1}}KernSmoothKernSmooth.
See the examples for how to use this function together with
pairs.
bkde2D from package \href{https://CRAN.R-project.org/package=#1}{\pkg{#1}}KernSmoothKernSmooth;
densCols which uses the same smoothing computations and
blues9 in package grDevices. scatter.smooth adds a loess
regression smoother to a scatter plot.