# maxnndist

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

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

##### 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`

.

##### See Also

##### 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)*