sm (version 2.0-2)

nnbr: nearest neighbour distances from data in one or two dimensions

Description

This function calculates the k nearest neighbour distance from each value in x to the remainder of the data. In two dimensions, Euclidean distance is used after standardising the data to have unit variance in each component.

Usage

nnbr(x, k)

Arguments

x

the vector, or two-column matrix, of data.

k

the required order of nearest neighbour.

Value

• the vector of nearest neighbour distances.

Details

see Section 1.7.1 of the reference below.

References

Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations. Oxford University Press, Oxford.

See Also

none.

Examples

x  <- rnorm(50)
hw <- nnbr(x, 10)
hw <- hw/exp(mean(log(hw)))
sm.density(x, h.weights=hw)