Nonparametric tests of dependence between a spatial point process and a covariate

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A10452442" target="_blank" >RIV/00216208:11320/22:10452442 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.metma-x.udl.cat/proceedings" target="_blank" >http://www.metma-x.udl.cat/proceedings</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Nonparametric tests of dependence between a spatial point process and a covariate

Popis výsledku v původním jazyce

In this contribution we consider the problem of testing possible dependence between a point process and a spatial covariate. We recall the available methods which are based on the assumption of a Poissonprocess. Taking advantage of the recent development of the random shift methods we study the nonparametrictests using random shifts which are suitable also for non-Poisson processes. We study the performance of thedifferent tests in a simulation study and conclude that the random shift test, either with the toroidal correction or the variance correction, depending on the strength of interactions in the point process, performs well for non-Poisson processes.

Název v anglickém jazyce

Nonparametric tests of dependence between a spatial point process and a covariate

Popis výsledku anglicky

In this contribution we consider the problem of testing possible dependence between a point process and a spatial covariate. We recall the available methods which are based on the assumption of a Poissonprocess. Taking advantage of the recent development of the random shift methods we study the nonparametrictests using random shifts which are suitable also for non-Poisson processes. We study the performance of thedifferent tests in a simulation study and conclude that the random shift test, either with the toroidal correction or the variance correction, depending on the strength of interactions in the point process, performs well for non-Poisson processes.

Druh

O - Ostatní výsledky

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GA19-04412S" target="_blank" >GA19-04412S: Nové přístupy k modelování a statistice náhodných množin</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů