Nonparametric testing of the dependence structure among points-marks-covariates in spatial point patterns

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12510%2F22%3A43904399" target="_blank" >RIV/60076658:12510/22:43904399 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11320/22:10452142

Výsledek na webu

<a href="https://onlinelibrary.wiley.com/doi/10.1111/insr.12503" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1111/insr.12503</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/insr.12503" target="_blank" >10.1111/insr.12503</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Nonparametric testing of the dependence structure among points-marks-covariates in spatial point patterns

Popis výsledku v původním jazyce

We investigate testing of the hypothesis of independence between a covariate and the marks in a marked point process. It would be rather straightforward if the (unmarked) point process were independent of the covariate and the marks. In practice, however, such an assumption is questionable and possible dependence between the point process and the covariate or the marks may lead to incorrect conclusions. Therefore, we propose to investigate the complete dependence structure in the triangle points–marks–covariates together. We take advantage of the recent development of the nonparametric random shift methods, namely, the new variance correction approach, and propose tests of the null hypothesis of independence between the marks and the covariate and between the points and the covariate. We present a detailed simulation study showing the performance of the methods and provide two theorems establishing the appropriate form of the correction factors for the variance correction. Finally, we illustrate the use of the proposed methods in two real applications.

Název v anglickém jazyce

Nonparametric testing of the dependence structure among points-marks-covariates in spatial point patterns

Popis výsledku anglicky

We investigate testing of the hypothesis of independence between a covariate and the marks in a marked point process. It would be rather straightforward if the (unmarked) point process were independent of the covariate and the marks. In practice, however, such an assumption is questionable and possible dependence between the point process and the covariate or the marks may lead to incorrect conclusions. Therefore, we propose to investigate the complete dependence structure in the triangle points–marks–covariates together. We take advantage of the recent development of the nonparametric random shift methods, namely, the new variance correction approach, and propose tests of the null hypothesis of independence between the marks and the covariate and between the points and the covariate. We present a detailed simulation study showing the performance of the methods and provide two theorems establishing the appropriate form of the correction factors for the variance correction. Finally, we illustrate the use of the proposed methods in two real applications.

Druh

J_imp - Článek v periodiku v databázi Web of Science

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

Název periodika

International Statistical Review

ISSN

0306-7734

e-ISSN

1751-5823

Svazek periodika

90

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

30

Strana od-do

592-621

Kód UT WoS článku

000796146100001

EID výsledku v databázi Scopus

2-s2.0-85132599858