| 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)