# clarkevans

##### Clark and Evans Aggregation Index

Computes the Clark and Evans aggregation index $R$ for a spatial point pattern.

- Keywords
- spatial, nonparametric

##### Usage

```
clarkevans(X, correction=c("none", "Donnelly", "guard"),
clipregion=NULL)
```

##### Arguments

- X
- A spatial point pattern (object of class
`"ppp"`

). - correction
- Character vector. The type of edge correction(s) to be applied.
- clipregion
- Optional. Clipping region for the guard area correction.
A window (object of class
`"owin"`

). See Details.

##### Details

The Clark and Evans (1954) aggregation index $R$ is a crude measure of clustering or ordering of a point pattern. It is the ratio of the observed mean nearest neighbour distance in the pattern to that expected for a Poisson point process of the same intensity. A value $R>1$ suggests ordering, while $R<1$ suggests="" clustering.<="" p="">

Without correction for edge effects, the value of `R`

will be
positively biased. Edge effects arise because, for a point of `X`

close to the edge of the window, the true nearest neighbour may
actually lie outside the window. Hence observed nearest neighbour
distances tend to be larger than the true nearest neighbour distances.

The argument `correction`

specifies an edge correction
or several edge corrections to be applied. It is a character vector
containing one or more of the options `"none"`

, `"Donnelly"`

and `"guard"`

(which are recognised by partial matching).
These edge corrections are:
[object Object],[object Object],[object Object]

##### Value

- A numeric value or numeric vector, with named components
naive $R$ without edge correction edge $R$ using Donnelly edge correction guard $R$ using guard region - (as selected by
`correction`

). The value of the`edge`

component will be`NA`

if the window of`X`

is not a rectangle.

##### References

Clark, P.J. and Evans, F.C. (1954)
Distance to nearest neighbour as a measure of spatial
relationships in populations *Ecology* **35**,
445--453.

Donnelly, K. (1978) Simulations to determine the variance
and edge-effect of total nearest neighbour distance.
In *Simulation methods in archaeology*,
Cambridge University Press, pp 91--95.

##### See Also

##### Examples

```
# Example of a clustered pattern
data(redwood)
clarkevans(redwood)
# Example of an ordered pattern
data(cells)
clarkevans(cells)
# Random pattern
X <- rpoispp(100)
clarkevans(X)
```

*Documentation reproduced from package spatstat, version 1.11-7, License: GPL version 2 or newer*