Returns the theoretical \(K\) function or the pair correlation function of a cluster point process model or Cox point process model.

```
# S3 method for kppm
Kmodel(model, …)
``` # S3 method for kppm
pcfmodel(model, …)

model

A fitted cluster point process model (object of
class `"kppm"`

) typically obtained from
the model-fitting algorithm `kppm`

.

…

Ignored.

A `function`

in the R language,
which takes one argument `r`

.

For certain types of point process models, it is possible to
write down a mathematical expression for the \(K\) function
or the pair correlation function of the model. In particular this
is possible for a fitted cluster point process model
(object of class `"kppm"`

obtained from `kppm`

).

The functions `Kmodel`

and `pcfmodel`

are generic.
The functions documented here are the methods for the class `"kppm"`

.

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.

`Kest`

or `pcf`

to estimate the \(K\) function or pair correlation function
nonparametrically from data.

`kppm`

to fit cluster models.

`Kmodel`

for the generic functions.

`Kmodel.ppm`

for the method for Gibbs processes.

# NOT RUN { data(redwood) fit <- kppm(redwood, ~x, "MatClust") K <- Kmodel(fit) K(c(0.1, 0.2)) curve(K(x), from=0, to=0.25) # }