Truncated kernel density derivative estimate

Truncated kernel density derivative estimate for 2-dimensional data.

Usage

kde.truncate(fhat, boundary) 
kdde.truncate(fhat, boundary)

Arguments

fhat: object of class kde or kdde
boundary: two column matrix delimiting the boundary for truncation

Value

A truncated kernel density (derivative) estimate inherits the same object class as the input estimate.

Details

A simple truncation is performed on the kernel estimator. All the points in the estimation grid which are outside of the regions delimited by boundary are set to 0, and their probability mass is distributed proportionally to the remaining density (derivative) values.

Examples

data(worldbank)
wb <- as.matrix(na.omit(worldbank[,c("internet", "ag.value")]))
fhat <- kde(x=wb)
rectb <- cbind(x=c(0,100,100,0,0), y=c(0,0,100,100,0))
fhat.b <- kde.truncate(fhat, boundary=rectb)
plot(fhat, col=1, xlim=c(0,100), ylim=c(0,100))
plot(fhat.b, add=TRUE, col=4)
rect(0,0,100,100, lty=2)


library(oz)
data(grevillea)
wa.coast <- ozRegion(section=1)
wa.polygon <- cbind(wa.coast$lines[[1]]$x, wa.coast$lines[[1]]$y)
fhat1 <- kdde(x=grevillea, deriv.order=1)
fhat1 <- kdde.truncate(fhat1, wa.polygon)
oz(section=1, xlim=c(113,122), ylim=c(-36,-29))
plot(fhat1, add=TRUE, display="filled.contour")