panysib {spatstat.model} | R Documentation |
Probability that a Point Has Any Siblings
Description
Given a cluster process model, calculate the probability that a point of the process has any siblings.
Usage
panysib(object)
Arguments
object |
Fitted cluster process model (object of class |
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. This function computes the probability that a
given random point has any
siblings.
If object
is a stationary point process, the result is a single
number, which is the probability that a typical point of the process
has any siblings.
If this number is small,
then the process is approximately a homogeneous Poisson process
(complete spatial randomness). The converse is not true (Baddeley et al, 2022).
Otherwise, the result is a pixel image, in which the value at any
location u
is the conditional probability,
given there is a point of the
process at u
, that this point has any siblings.
If the pixel values are all small,
then the process is approximately an inhomogeneous Poisson process.
This concept was proposed by Baddeley et al (2022).
Value
A single number (if object
is a stationary point process)
or a pixel image (otherwise).
Author(s)
Adrian Baddeley Adrian.Baddeley@curtin.edu.au.
References
Baddeley, A., Davies, T.M., Hazelton, M.L., Rakshit, S. and Turner, R.
(2022)
Fundamental problems in fitting spatial cluster process models.
Spatial Statistics 52, 100709.
DOI: 10.1016/j.spasta.2022.100709
See Also
Examples
fit <- kppm(redwood ~ polynom(x,y,2))
plot(panysib(fit))