# nndist.ppx

0th

Percentile

##### Nearest Neighbour Distances in Any Dimensions

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

Keywords
spatial, math
##### Usage
## S3 method for class 'ppx':
nndist(X, \dots, k=1)
##### Arguments
X
Multi-dimensional point pattern (object of class "ppx").
...
Arguments passed to coords.ppx to determine which coordinates should be used.
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 multi-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.ppx is the method for the class "ppx".

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 find the nearest neighbour distances from one point pattern to another point pattern, use nncross. By default, both spatial and temporal coordinates are extracted. To obtain the spatial distance between points in a space-time point pattern, set temporal=FALSE.

##### 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, nnwhich

• nndist.ppx
##### Examples
df <- data.frame(x=runif(5),y=runif(5),z=runif(5),w=runif(5))
X <- ppx(data=df)

# 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 1.18-4, License: GPL (>= 2)

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