A Statistical Test for Ripley’s greater Function Rejection of Poisson Null Hypothesis
Résumé
textlessptextgreater Ripley's textlessmath id="M2"textgreater textlessmrowtextgreater textlessmitextgreaterKtextless/mitextgreater textless/mrowtextgreater textless/mathtextgreater function is the classical tool to characterize the spatial structure of point patterns. It is widely used in vegetation studies. Testing its values against a null hypothesis usually relies on Monte-Carlo simulations since little is known about its distribution. We introduce a statistical test against complete spatial randomness (CSR). The test returns the textlessmath id="M3"textgreater textlessmrowtextgreater textlessmitextgreaterPtextless/mitextgreater textless/mrowtextgreater textless/mathtextgreater value to reject the null hypothesis of independence between point locations. It is more rigorous and faster than classical Monte-Carlo simulations. We show how to apply it to a tropical forest plot. The necessary R code is provided. textless/ptextgreater
Auteurs, date et publication :
Auteurs Eric Marcon , Stéphane Traissac , Gabriel Lang
Publication : Ecology
Date : 2023
Volume : 2013
Pages : 1–9