# psib

##### Sibling Probability of Cluster Point Process

Computes the sibling probability of a cluster point process model.

##### Usage

`psib(object)` # S3 method for kppm
psib(object)

##### Arguments

- object
Fitted cluster point process model (object of class

`"kppm"`

).

##### Details

In a Poisson cluster process, two points are called *siblings*
if they belong to the same cluster, that is, if they had the same
parent point. If two points of the process are
separated by a distance \(r\), the probability that
they are siblings is \(p(r) = 1 - 1/g(r)\) where \(g\) is the
pair correlation function of the process.

The value \(p(0) = 1 - 1/g(0)\) is the probability that, if two points of the process are situated very close to each other, they came from the same cluster. This probability is an index of the strength of clustering, with high values suggesting strong clustering.

This concept was proposed in Baddeley, Rubak and Turner (2015, page 479) and Baddeley (2017).

##### Value

A single number.

##### References

Baddeley, A. (2017)
Local composite likelihood for spatial point processes.
*Spatial Statistics* **22**, 261--295.

Baddeley, A., Rubak, E. and Turner, R. (2015)
*Spatial Point Patterns: Methodology and Applications with R*.
Chapman and Hall/CRC Press.

##### See Also

##### Examples

```
# NOT RUN {
fit <- kppm(redwood ~1, "Thomas")
psib(fit)
# }
```

*Documentation reproduced from package spatstat, version 1.64-1, License: GPL (>= 2)*