# clusterradius

##### Compute or Extract Effective Range of Cluster Kernel

Given a cluster point process model, this command returns a value beyond which the the probability density of the cluster offspring is neglible.

- Keywords
- spatial

##### Usage

`clusterradius(model, ...)`## S3 method for class 'kppm':
clusterradius(model, \dots, thresh = NULL, precision = FALSE)

## S3 method for class 'character':
clusterradius(model, \dots, thresh = NULL, precision = FALSE)

##### Arguments

- model
- Cluster model. Either a fitted cluster or Cox model
(object of class
`"kppm"`

), or a character string specifying the type of cluster model. - ...
- Parameter values for the model,
when
`model`

is a character string. - thresh
- Numerical threshold relative to the cluster kernel value at the origin (parent location) determining when the cluster kernel will be considered neglible. A sensible default is provided.
- precision
- Logical. If
`precision=TRUE`

the precision of the calculated range is returned as an attribute to the range. See details.

##### Details

Given a cluster model this function by default returns the effective
range of the model with the given parameters as used in spatstat. For
the Matern cluster model (see e.g. `rMatClust`

) this is
simply the finite radius of the offsring density given by the paramter
`scale`

irrespective of other options given to this function. The
remaining models in spatstat have infinite theoretical range, and an
effective finite value is given as follows: For the Thomas model (see
e.g. `rThomas`

the default is `4*scale`

where scale
is the scale or standard deviation parameter of the model. If
`thresh`

is given the value is instead found as described for the
other models below.

For the Cauchy model (see e.g. `rCauchy`

) and the Variance
Gamma (Bessel) model (see e.g. `rVarGamma`

) the value of
`thresh`

defaults to 0.001, and then this is used to compute the
range numerically as follows. If $k(x,y)=k_0(r)$ with $r=\sqrt(x^2+y^2)$
denotes the isotropic cluster kernel then $f(r) = 2 \pi r
k_0(r)$ is the
density function of the offspring distance from the parent. The range
is determined as the value of $r$ where $f(r)$ falls below
`thresh`

times $k_0(r)$.
If `precision=TRUE`

the precision related to the chosen range is
returned as an attribute. Here the precision is defined as the polar
integral of the kernel from distance 0 to the calculated
range. Ideally this should be close to the value 1 which would be
obtained for the true theretical infinite range.

##### Value

- A positive numeric.
Additionally, the precision related to this range value is returned as an attribute

`"prec"`

, if`precision=TRUE`

.

##### See Also

`clusterkernel`

, `kppm`

,
`rMatClust`

, `rThomas`

, `rCauchy`

,
`rVarGamma`

, `rNeymanScott`

.

##### Examples

```
fit <- kppm(redwood ~ x, "MatClust")
clusterradius(fit)
clusterradius("Thomas", scale = .1)
clusterradius("Thomas", scale = .1, thresh = 0.001)
clusterradius("VarGamma", scale = .1, nu = 2, precision = TRUE)
```

*Documentation reproduced from package spatstat, version 1.42-2, License: GPL (>= 2)*