spatstat (version 1.33-0)

intensity.ppm: Intensity of Fitted Point Process Model

Description

Computes the intensity of a fitted point process model.

Usage

## S3 method for class 'ppm':
intensity(X, ...)

Arguments

X

A fitted point process model (object of class "ppm").

...

Arguments passed to predict.ppm in some cases. See Details.

Value

• A numeric value (if the model is stationary) or a pixel image.

Details

This is a method for the generic function intensity for fitted point process models (class "ppm").

The intensity of a point process model is the expected number of random points per unit area.

If X is a Poisson point process model, the intensity of the process is computed exactly. The result is a numerical value if X is a stationary Poisson point process, and a pixel image if X is non-stationary. (In the latter case, the resolution of the pixel image is controlled by the arguments ... which are passed to predict.ppm.)

If X is another Gibbs point process model, the intensity is computed approximately using the Poisson-saddlepoint approximation (Baddeley and Nair, 2012). Currently this is implemented only for pairwise interactions.

References

Baddeley, A. and Nair, G. (2012) Fast approximation of the intensity of Gibbs point processes. Electronic Journal of Statistics 6 1155--1169.

See Also

intensity, intensity.ppp

Examples

fitP <- ppm(swedishpines, ~1, Poisson())
  intensity(fitP)
  fitS <- ppm(swedishpines, ~1, Strauss(9))
  intensity(fitS)