# maxnndist

0th

Percentile

##### Compute Minimum or Maximum Nearest-Neighbour Distance

A faster way to compute the minimum or maximum nearest-neighbour distance in a point pattern.

Keywords
spatial, math
##### Usage
minnndist(X, positive=FALSE, by=NULL)
maxnndist(X, positive=FALSE, by=NULL)
##### Arguments
X

A point pattern (object of class "ppp").

positive

Logical. If FALSE (the default), compute the usual nearest-neighbour distance. If TRUE, ignore coincident points, so that the nearest neighbour distance for each point is greater than zero.

by

Optional. A factor, which separates X into groups. The algorithm will compute the distance to the nearest point in each group.

##### Details

These functions find the minimum and maximum values of nearest-neighbour distances in the point pattern X. minnndist(X) and maxnndist(X) are equivalent to, but faster than, min(nndist(X)) and max(nndist(X)) respectively.

The value is NA if npoints(X) < 2.

##### Value

A single numeric value (possibly NA).

If by is given, the result is a numeric matrix giving the minimum or maximum nearest neighbour distance between each subset of X.

nndist

• maxnndist
• minnndist
##### Examples
# NOT RUN {
min(nndist(swedishpines))
minnndist(swedishpines)

max(nndist(swedishpines))
maxnndist(swedishpines)

minnndist(lansing, positive=TRUE)

if(interactive()) {
X <- rpoispp(1e6)
system.time(min(nndist(X)))
system.time(minnndist(X))
}

minnndist(amacrine, by=marks(amacrine))
maxnndist(amacrine, by=marks(amacrine))
# }

Documentation reproduced from package spatstat, version 1.64-1, License: GPL (>= 2)

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