Poisson: Poisson Point Process Model

In spatstat.model: Parametric Statistical Modelling and Inference for the 'spatstat' Family

Poisson Point Process Model

Description

Creates an instance of the Poisson point process model which can then be fitted to point pattern data.

Usage

 Poisson()

Details

The function ppm, which fits point process models to point pattern data, requires an argument interaction of class "interact" describing the interpoint interaction structure of the model to be fitted. The appropriate description of the Poisson process is provided by the value of the function Poisson.

This works for all types of Poisson processes including multitype and nonstationary Poisson processes.

Value

An object of class "interact" describing the interpoint interaction structure of the Poisson point process (namely, there are no interactions).

Author(s)

\spatstatAuthors

See Also

ppm, Strauss

Examples

 ppm(nztrees ~1, Poisson())
 # fit the stationary Poisson process to 'nztrees'
 # no edge correction needed

 lon <- longleaf
 
 longadult <- unmark(subset(lon, marks >= 30))
 ppm(longadult ~ x, Poisson())
 # fit the nonstationary Poisson process 
 # with intensity lambda(x,y) = exp( a + bx)

 # trees marked by species
 lans <- lansing
 
 ppm(lans ~ marks, Poisson())
 # fit stationary marked Poisson process
 # with different intensity for each species

 
   ppm(lansing ~ marks * polynom(x,y,3), Poisson())
   # fit nonstationary marked Poisson process
   # with different log-cubic trend for each species
 
 

spatstat.model documentation built on Sept. 30, 2024, 9:26 a.m.