Kmodel.ppm | R Documentation |
Returns the theoretical K function or the pair correlation function of a fitted Gibbs point process model.
## S3 method for class 'ppm' Kmodel(model, ...) ## S3 method for class 'ppm' pcfmodel(model, ...)
model |
A fitted Poisson or Gibbs point process model (object of
class |
... |
Ignored. |
This function computes an approximation to the K function or the pair correlation function of a Gibbs point process.
The functions Kmodel
and pcfmodel
are generic.
The functions documented here are the methods for the class
"ppm"
.
The approximation is only available for stationary pairwise-interaction models. It uses the second order Poisson-saddlepoint approximation (Baddeley and Nair, 2012b) which is a combination of the Poisson-Boltzmann-Emden and Percus-Yevick approximations.
The return value is a function
in the R language,
which takes one argument r
.
Evaluation of this function, on a numeric vector r
,
yields values of the desired K function or pair correlation
function at these distance values.
A function
in the R language,
which takes one argument r
.
and Gopalan Nair.
Baddeley, A. and Nair, G. (2012a) Fast approximation of the intensity of Gibbs point processes. Electronic Journal of Statistics 6 1155–1169.
Baddeley, A. and Nair, G. (2012b)
Approximating the moments of a spatial point process.
Stat 1, 1, 18–30.
DOI: 10.1002/sta4.5
Kest
or pcf
to estimate the K function or pair correlation function
nonparametrically from data.
ppm
to fit Gibbs models.
Kmodel
for the generic functions.
Kmodel.kppm
for the method for cluster/Cox processes.
fit <- ppm(swedishpines, ~1, Strauss(8)) p <- pcfmodel(fit) K <- Kmodel(fit) p(6) K(8) curve(K(x), from=0, to=15)
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