spatstat.model (version 3.3-5)

intensity.slrm: Intensity of Fitted Spatial Logistic Regression Model

Description

Computes the intensity of a fitted spatial logistic regression model, treated as a point process model.

Usage

# S3 method for slrm
intensity(X, ...)

Value

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

Arguments

X

A fitted spatial logistic regression model (object of class "slrm").

...

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

Author

Adrian Baddeley , Rolf Turner and Ege Rubak .

Details

This is a method for the generic function intensity for spatial logistic regression models (class "slrm").

The fitted spatial logistic regression model X is interpreted as a point process model. The intensity of a point process model is defined as the expected number of random points per unit area. The fitted probabilities of presence according to X are converted to intensity values.

The result is a numerical value if X is stationary, 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.slrm.

References

Baddeley, A., Berman, M., Fisher, N.I., Hardegen, A., Milne, R.K., Schuhmacher, D., Shah, R. and Turner, R. (2010) Spatial logistic regression and change-of-support for spatial Poisson point processes. Electronic Journal of Statistics 4, 1151--1201. DOI: 10.1214/10-EJS581

See Also

intensity, intensity.ppm

Examples

  fitS <- slrm(swedishpines ~ 1)
  intensity(fitS)
  fitX <- slrm(swedishpines ~ x)
  intensity(fitX)