R: nearest neighbour distances from data in one or two...

nnbr {sm} | R Documentation

## 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.

### Details

see Section 1.7.1 of the reference below.

### Value

the vector of nearest neighbour distances.

### 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)

[Package sm version 2.2-5.4 Index]