# nndist.pp3

0th

Percentile

##### Nearest neighbour distances in three dimensions

Computes the distance from each point to its nearest neighbour in a three-dimensional point pattern. Alternatively computes the distance to the second nearest neighbour, or third nearest, etc.

Keywords
spatial, math
##### Usage
## S3 method for class 'pp3':
nndist(X, \dots, k=1)
##### Arguments
X
Three-dimensional point pattern (object of class "pp3").
...
Ignored.
k
Integer, or integer vector. The algorithm will compute the distance to the kth nearest neighbour.
##### Details

This function computes the Euclidean distance from each point in a three-dimensional point pattern to its nearest neighbour (the nearest other point of the pattern). If k is specified, it computes the distance to the kth nearest neighbour.

The function nndist is generic; this function nndist.pp3 is the method for the class "pp3".

The argument k may be a single integer, or an integer vector. If it is a vector, then the $k$th nearest neighbour distances are computed for each value of $k$ specified in the vector.

If there is only one point (if x has length 1), then a nearest neighbour distance of Inf is returned. If there are no points (if x has length zero) a numeric vector of length zero is returned.

To identify which point is the nearest neighbour of a given point, use nnwhich.

To use the nearest neighbour distances for statistical inference, it is often advisable to use the edge-corrected empirical distribution, computed by G3est.

To find the nearest neighbour distances from one point pattern to another point pattern, use nncross.

##### Value

• Numeric vector or matrix containing the nearest neighbour distances for each point.

If k = 1 (the default), the return value is a numeric vector v such that v[i] is the nearest neighbour distance for the ith data point. If k is a single integer, then the return value is a numeric vector v such that v[i] is the kth nearest neighbour distance for the ith data point.

If k is a vector, then the return value is a matrix m such that m[i,j] is the k[j]th nearest neighbour distance for the ith data point.

##### Warnings

An infinite or NA value is returned if the distance is not defined (e.g. if there is only one point in the point pattern).

nndist, pairdist, G3est, nnwhich

• nndist.pp3
##### Examples
X <- runifpoint3(40)

# nearest neighbours
d <- nndist(X)

# second nearest neighbours
d2 <- nndist(X, k=2)

# first, second and third nearest
d1to3 <- nndist(X, k=1:3)
Documentation reproduced from package spatstat, version 1.18-1, License: GPL (>= 2)

### Community examples

Looks like there are no examples yet.