# summary.kppm

##### Summarizing a Fitted Cox or Cluster Point Process Model

`summary`

method for class `"kppm"`

.

##### Usage

```
# S3 method for kppm
summary(object, …, quick=FALSE)
``` # S3 method for summary.kppm
print(x, …)

##### Arguments

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

`"kppm"`

).- quick
Logical value controlling the scope of the summary.

- …
Arguments passed to

`summary.ppm`

or`print.summary.ppm`

controlling the treatment of the trend component of the model.- x
Object of class

`"summary.kppm"`

as returned by`summary.kppm`

.

##### Details

This is a method for the generic `summary`

for the class `"kppm"`

. An object of class `"kppm"`

describes a fitted Cox or cluster point process model.
See `kppm`

.

`summary.kppm`

extracts information about the
type of model that has been fitted, the data to which the model was
fitted, and the values of the fitted coefficients.

`print.summary.kppm`

prints this information in a
comprehensible format.

In normal usage, `print.summary.kppm`

is invoked implicitly
when the user calls `summary.kppm`

without assigning its value
to anything. See the examples.

You can also type `coef(summary(object))`

to extract a table
of the fitted coefficients of the point process model `object`

together with standard errors and confidence limits.

##### Value

`summary.kppm`

returns an object of class `"summary.kppm"`

,
while `print.summary.kppm`

returns `NULL`

.

The result of `summary.kppm`

includes at least the
following components:

character string name of the original point pattern data

logical value indicating whether the model is stationary

the `clusters`

argument to `kppm`

character string describing the model

`TRUE`

if the model is a Poisson cluster process,
`FALSE`

if it is a log-Gaussian Cox process

Estimated intensity: numeric value, or pixel image

Mean cluster size: numeric value, pixel image, or
`NULL`

list of fitted parameters for the cluster model

list of fixed parameters for the cluster model, if any

character string representing the original call to
`kppm`

##### Examples

```
# NOT RUN {
fit <- kppm(redwood ~ 1, "Thomas")
summary(fit)
coef(summary(fit))
# }
```

*Documentation reproduced from package spatstat, version 1.56-1, License: GPL (>= 2)*