spatstat (version 1.28-1)

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).

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)