R: Prediction from a Fitted Cluster Point Process Model

predict.kppm {spatstat.core} | R Documentation

## Prediction from a Fitted Cluster Point Process Model

### Description

Given a fitted cluster point process model, these functions compute the fitted intensity.

### Usage

      ## S3 method for class 'kppm'
    fitted(object, ...)

      ## S3 method for class 'kppm'
    predict(object, ...)

### Arguments

`object` | Fitted cluster point process model. An object of class `"kppm"`.
`...` | Arguments passed to `fitted.ppm` or `predict.ppm` respectively.

### Details

These functions are methods for the generic functions `fitted` and `predict`. The argument `object` should be a cluster point process model (object of class `"kppm"`) obtained using the function `kppm`.

The intensity of the fitted model is computed, using `fitted.ppm` or `predict.ppm` respectively.

### Value

The value of `fitted.kppm` is a numeric vector giving the fitted values at the quadrature points.

The value of `predict.kppm` is usually a pixel image (object of class `"im"`), but see `predict.ppm` for details.

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au

and Rolf Turner r.turner@auckland.ac.nz

### See Also

`kppm`, `plot.kppm`, `vcov.kppm`, `fitted.ppm`, `predict.ppm`

### Examples

      data(redwood)
      fit <- kppm(redwood ~ x, "Thomas")
      predict(fit)

[Package spatstat.core version 2.4-4 Index]