R: Determine the Order of Interpoint Interaction in a Model

interactionorder {spatstat.core} | R Documentation

## Determine the Order of Interpoint Interaction in a Model

### Description

Given a point process model, report the order of interpoint interaction.

### Usage

    interactionorder(object)

    ## S3 method for class 'ppm'
    interactionorder(object)

    ## S3 method for class 'interact'
    interactionorder(object)

    ## S3 method for class 'isf'
    interactionorder(object)

    ## S3 method for class 'fii'
    interactionorder(object)

### Arguments

`object` | A point process model (class `"ppm"`) or similar information.

### Details

This function determines the order of interpoint interaction in a Gibbs point process model (or a related object).

The interaction order is defined as the largest number `k` such that the probability density of the model contains terms involving `k` points at a time. For example, in a pairwise interaction process such as the Strauss process, the probability density contains interaction terms between each pair of points, but does not contain any terms that involve three points at a time, so the interaction order is 2.

Poisson point processes have interaction order 1. Pairwise-interaction processes have interaction order 2. Point processes with the triplet interaction `Triplets` have interaction order 3. The Geyer saturation model `Geyer` and the area-interaction model `AreaInter` have infinite order of interaction.

### Value

A positive integer, or `Inf`.

### Author(s)

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

### Examples

      interactionorder(ppm(cells ~ 1))
      interactionorder(Strauss(0.1))
      interactionorder(Triplets(0.1))
      interactionorder(Geyer(0.1, 2))
      interactionorder(Hybrid(Strauss(0.1), Triplets(0.2)))

[Package spatstat.core version 2.4-4 Index]