spatstat.core: quadrat.test.splitppp – R documentation

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quadrat.test.splitppp

Dispersion Test of CSR for Split Point Pattern Based on Quadrat Counts

Description

Performs a test of Complete Spatial Randomness for each of the component patterns in a split point pattern, based on quadrat counts. By default performs chi-squared tests; can also perform Monte Carlo based tests.

Usage

## S3 method for class 'splitppp'
quadrat.test(X, ..., df=NULL, df.est=NULL, Xname=NULL)

Arguments

`X`	A split point pattern (object of class `"splitppp"`), each component of which will be subjected to the goodness-of-fit test.
`...`	Arguments passed to `quadrat.test.ppp`.
`df,df.est,Xname`	Arguments passed to `pool.quadrattest`.

Details

The function quadrat.test is generic, with methods for point patterns (class "ppp"), split point patterns (class "splitppp") and point process models (class "ppm").

If X is a split point pattern, then for each of the component point patterns (taken separately) we test the null hypotheses of Complete Spatial Randomness, then combine the result into a single test.

The method quadrat.test.ppp is applied to each component point pattern. Then the results are pooled using pool.quadrattest to obtain a single test.

Value

An object of class "quadrattest" which can be printed and plotted.

Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au

and Rolf Turner r.turner@auckland.ac.nz

Examples

data(humberside)
 qH <- quadrat.test(split(humberside), 2, 3)
 plot(qH)
 qH

spatstat.core

Core Functionality of the 'spatstat' Family

v2.1-2

GPL (>= 2)

Authors

Adrian Baddeley [aut, cre], Rolf Turner [aut], Ege Rubak [aut], Kasper Klitgaard Berthelsen [ctb], Achmad Choiruddin [ctb], Jean-Francois Coeurjolly [ctb], Ottmar Cronie [ctb], Tilman Davies [ctb], Julian Gilbey [ctb], Yongtao Guan [ctb], Ute Hahn [ctb], Kassel Hingee [ctb], Abdollah Jalilian [ctb], Marie-Colette van Lieshout [ctb], Greg McSwiggan [ctb], Tuomas Rajala [ctb], Suman Rakshit [ctb], Dominic Schuhmacher [ctb], Rasmus Plenge Waagepetersen [ctb], Hangsheng Wang [ctb]

Initial release

2021-04-17