ksupp {ks} | R Documentation |
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 |
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 |
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
Examples
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)