nnbr function

nearest neighbour distances from data in one or two dimensions

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.

nnbr(x, k)

Arguments

• x: the vector, or two-column matrix, of data.
• k: the required order of nearest neighbour.

Returns

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)