ksupp: Kernel support estimate

In ks: Kernel Smoothing

Kernel support estimate

Description

Kernel support estimate for 2 and 3-dimensional data.

Usage

ksupp(fhat, cont=95, abs.cont, convex.hull=TRUE)

## S3 method for class 'ksupp'
plot(x, display="plot3D", ...)

Arguments

fhat	object of class kde
cont	percentage for contour level curve. Default is 95.
abs.cont	absolute density estimate height for contour level curve
convex.hull	flag to compute convex hull of contour level curve. Default is TRUE.
x	object of class ksupp
display	one of "plot3D", "rgl" (required for 3-d only)
...	other graphics parameters

Details

The kernel support estimate is the level set of the density estimate that exceeds the cont percent contour level. If this level set is a simply connected region, then this can suffice to be a conservative estimate of the density support. Otherwise, the convex hull of the level set is advised. For 2-d data, the convex hull is computed by chull; for 3-d data, it is computed by geometry::convhulln.

Value

A kernel support estimate is an object of class ksupp, i.e. a 2- or 3-column matrix which delimits the (convex hull of the) level set of the density estimate fhat.

See Also

kde

Examples

library(oz)
data(grevillea)
fhat <- kde(x=grevillea)
fhat.supp <- ksupp(fhat)
plot(fhat, display="filled.contour", cont=seq(10,90,by=10))
plot(fhat, cont=95, add=TRUE, col=1)
plot(fhat.supp,  lty=2)

data(iris)
fhat <- kde(x=iris[,1:3])
fhat.supp <- ksupp(fhat)
plot(fhat)
plot(fhat.supp, add=TRUE, col=3, alpha=0.1)

ks documentation built on Aug. 11, 2023, 1:10 a.m.