clarkevans.test
Clark and Evans Test
Performs the Clark-Evans test of aggregation for a spatial point pattern.
- Keywords
- spatial, nonparametric
Usage
clarkevans.test(X, ...,
correction="none",
clipregion=NULL,
alternative=c("two.sided", "less", "greater"),
nsim=1000)
Arguments
- X
- A spatial point pattern (object of class
"ppp"
). - ...
- Ignored.
- correction
- Character string.
The type of edge correction to be applied.
See
clarkevans
- clipregion
- Clipping region for the guard area correction.
A window (object of class
"owin"
). Seeclarkevans
- alternative
- String indicating the type of alternative for the hypothesis test.
- nsim
- Number of Monte Carlo simulations to perform, if a Monte Carlo p-value is required.
Details
This command uses the Clark and Evans (1954) aggregation index $R$
as the basis for a crude test of clustering or ordering of a point pattern.
The Clark-Evans index is computed by the function
clarkevans
. See the help for clarkevans
for information about the Clark-Evans index $R$ and about
the arguments correction
and clipregion
.
This command performs a hypothesis test of clustering or ordering of
the point pattern X
. The null hypothesis is Complete
Spatial Randomness, i.e. a uniform Poisson process. The alternative
hypothesis is specified by the argument alternative
:
alternative="less"
oralternative="clustered"
: the alternative hypothesis is that$R < 1$corresponding to a clustered point pattern;alternative="greater"
oralternative="regular"
: the alternative hypothesis is that$R > 1$corresponding to a regular or ordered point pattern;alternative="two.sided"
: the alternative hypothesis is that$R \neq 1$corresponding to a clustered or regular pattern.
clarkevans
. If correction="none"
,
the $p$-value for the test is computed by standardising
$R$ as proposed by Clark and Evans (1954) and referring the
statistic to the standard Normal distribution.
For other edge corrections, the $p$-value for the test is computed
by Monte Carlo simulation of nsim
realisations of
Complete Spatial Randomness.
Value
- An object of class
"htest"
representing the result of the test.
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.test(redwood)
clarkevans.test(redwood, alternative="less")