R: Summarizing a Fitted Cox or Cluster Point Process Model

summary.kppm {spatstat.core} | R Documentation

## Summarizing a Fitted Cox or Cluster Point Process Model

### Description

`summary` method for class `"kppm"`.

### Usage

      ## S3 method for class 'kppm'
    summary(object, ..., quick=FALSE)

      ## S3 method for class '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:

`Xname` | character string name of the original point pattern data
`stationary` | logical value indicating whether the model is stationary
`clusters` | the `clusters` argument to `kppm`
`modelname` | character string describing the model
`isPCP` | `TRUE` if the model is a Poisson cluster process, `FALSE` if it is a log-Gaussian Cox process
`lambda` | Estimated intensity: numeric value, or pixel image
`mu` | Mean cluster size: numeric value, pixel image, or `NULL`
`clustpar` | list of fitted parameters for the cluster model
`clustargs` | list of fixed parameters for the cluster model, if any
`callstring` | character string representing the original call to `kppm`

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk

### Examples

     fit <- kppm(redwood ~ 1, "Thomas")
     summary(fit)
     coef(summary(fit))

[Package spatstat.core version 2.4-4 Index]