nndist.pp3 {spatstat} | R Documentation |
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.
## S3 method for class 'pp3' nndist(X, ..., k=1)
X |
Three-dimensional point pattern
(object of class |
... |
Ignored. |
k |
Integer, or integer vector. The algorithm will compute the distance to the
|
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 k
th 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 kth 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
.
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 i
th data point.
If k
is a single integer, then the return value is a
numeric vector v
such that v[i]
is the
k
th nearest neighbour distance for the
i
th 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
i
th data point.
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).
Adrian Baddeley Adrian.Baddeley@csiro.au http://www.maths.uwa.edu.au/~adrian/ based on code for two dimensions by Pavel Grabarnik
nndist
,
pairdist
,
G3est
,
nnwhich
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)