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)
x |
the vector, or two-column matrix, of data. |
k |
the required order of nearest neighbour. |
see Section 1.7.1 of the reference below.
the vector of nearest neighbour distances.
Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations. Oxford University Press, Oxford.
none.
x <- rnorm(50) hw <- nnbr(x, 10) hw <- hw/exp(mean(log(hw))) sm.density(x, h.weights=hw)
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