hdrscatterplot {hdrcde} | R Documentation |
Scatterplot showing bivariate highest density regions
Description
Produces a scatterplot where the points are coloured according to the bivariate HDRs in which they fall.
Usage
hdrscatterplot(
x,
y,
levels = c(1, 50, 99),
kde.package = c("ash", "ks"),
noutliers = NULL,
label = NULL
)
Arguments
x |
Numeric vector or matrix with 2 columns. |
y |
Numeric vector of same length as |
levels |
Percentage coverage for HDRs |
kde.package |
Package to be used in calculating the kernel density
estimate when |
noutliers |
Number of outliers to be labelled. By default, all points outside the largest HDR are labelled. |
label |
Label of outliers of same length as |
Details
The bivariate density is estimated using kernel density estimation. Either
ash2
or kde
is used to do the
calculations. Then Hyndman's (1996) density quantile algorithm is used to
compute the HDRs. The scatterplot of (x,y) is created where the points are
coloured according to which HDR they fall. A ggplot object is returned.
Author(s)
Rob J Hyndman
See Also
Examples
x <- c(rnorm(200, 0, 1), rnorm(200, 4, 1))
y <- c(rnorm(200, 0, 1), rnorm(200, 4, 1))
hdrscatterplot(x, y)
hdrscatterplot(x, y, label = paste0("p", 1:length(x)))