# 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 class 'kppm':
Kmodel(model, \dots)
``` ## S3 method for class 'kppm':
pcfmodel(model, \dots)

##### 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 Rlanguage,
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 Rlanguage, 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

```
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 1.42-2, License: GPL (>= 2)*