hdr.boxplot.2d {hdrcde}R Documentation

Bivariate Highest Density Regions

Description

Calculates and plots highest density regions in two dimensions, including the bivariate HDR boxplot.

Usage

hdr.boxplot.2d(x, y, prob=c(0.01,0.50), h, show.points = FALSE, 
    xlab="", ylab="",  kde.package=c("ash","ks"), ...)

Arguments

x Numeric vector
y Numeric vector of same length as x.
prob Probability coverage required for HDRs
h Pair of bandwidths passed to either ash2 or kde. If missing, a reasonable default is used.
show.points If TRUE, will plot points over the top of contours.
xlab Label for x-axis.
ylab Label for y-axis.
kde.package Package to be used in calculating the kernel density estimate.
... Other arguments to be passed to plot.

Details

The 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.

Value

Some information about the HDRs is returned. See code for details.

Author(s)

Rob Hyndman

References

Hyndman, R.J. (1996) Computing and graphing highest density regions American Statistician, 50, 120-126.

See Also

hdr.boxplot

Examples

x <- c(rnorm(200,0,1),rnorm(200,4,1))
y <- c(rnorm(200,0,1),rnorm(200,4,1))
par(mfrow=c(1,2))
plot(x,y)
hdr.boxplot.2d(x,y)

[Package hdrcde version 2.09 Index]