# clarkevans

0th

Percentile

##### 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
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.

nndist, Gest

• clarkevans
##### 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)

# How to specify a clipping region
clip1 <- owin(c(0.1,0.9),c(0.1,0.9))
clip2 <- erode.owin(cells\$window, 0.1)
clarkevans(cells, clipregion=clip1)
clarkevans(cells, clipregion=clip2)
Documentation reproduced from package spatstat, version 1.12-5, License: GPL (>= 2)

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