R: Poisson Point Process Model

Poisson {spatstat.core} | R Documentation

## 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)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk

### 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

[Package spatstat.core version 1.65-5 Index]