density_points: denpoints
In anevolbap/ktaucenterscpp: Robust Clustering Procedures

Description Usage Arguments Details Value Author(s) References Examples

density_points Estimates the densities values of a sample.

1	density_points(data, neigh = 4)

`x`	A distance matrix calculated on `data` or a matrix
`k`	The number of nearest neighbors to calculate local point density

For a fixed y, density of y is defined as the sum of distance(y,z) on all z that are the k-nearest neighbors of y

dpoints

A real vector containing the density values for each point

Juan Domingo Gonzalez <juanrst@hotmail.com>

Hasan AM, et al. Robust partitional clustering by outlier and density insensitive seeding. Pattern Recognition Letters, 30(11), 994-1002, 2009.

## generate normal data in dimension 2
X <- matrix(rnorm(1000), ncol = 2)
a <- denpoints(x = X, k = 4)


## ten most isolated points
most_isolated = order(a)[1:10]

## plotting results: (most isolated points should be shown in green)
plot(X)
points(X[ most_isolated, ], pch = 19, col = 3)