# Kmodel.kppm

##### K Function or Pair Correlation Function of Cluster Model or Cox model

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

##### Usage

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

##### Arguments

- model
A fitted cluster point process model (object of class

`"kppm"`

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

.- …
Ignored.

##### Details

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.

##### Value

A `function`

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

.

##### See Also

`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.

##### Examples

```
# 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)
# }
```

*Documentation reproduced from package spatstat, version 1.57-1, License: GPL (>= 2)*