contourLevels {ks}R Documentation

Contour levels for kde and kda.kde objects

Description

Contour levels for kde and kda.kde objects.

Usage

contourLevels(x, ...)

## S3 method for class 'kde':
contourLevels(x, prob, cont, nlevels=5, ...)

## S3 method for class 'kda.kde':
contourLevels(x, prob, cont, nlevels=5, ...)

Arguments

x an object of class kde or kda.kde
prob vector of probabilities corresponding to highest density regions
cont vector of percentages which correspond to the complement of prob
nlevels number of pretty contour levels
... other parameters for contour

Details

The most straightfoward is to specify prob. Heights of the corresponding highest density region with probability prob are computed.

The cont parameter here is consistent with cont parameter from plot.kde and plot.kda.kde i.e. cont = (1 - prob)*100%.

If both prob and cont are missing then a pretty set of nlevels contours are computed.

Value

For kde objects, returns vector of heights. For kda.kde objects, returns a list of vectors, one for each training group.

See Also

contour, contourLines

Examples

## kde 
x <- rmvnorm.mixt(n=100, mus=c(0,0), Sigmas=diag(2), props=1)
Hx <- Hpi(x)
fhatx <- kde(x=x, H=Hx)
lev1 <- contourLevels(fhatx, prob=c(0.25, 0.5, 0.75))
lev2 <- contourLevels(fhatx, cont=c(75, 50, 25))      ## lev1 == lev2

## kda.kde
library(MASS)
data(iris)
ir <- iris[,1]
ir.gr <- iris[,5]
kda.fhat <- kda.kde(ir, ir.gr, hs=sqrt(c(0.01, 0.04, 0.07)))
contourLevels(kda.fhat, prob=c(0.25, 0.5, 0.75))

[Package ks version 1.6.2 Index]