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

Result code in 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>
Alternative codes found
RIV/00216208:11320/22:10452142
Result on the web
<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>

Result language
angličtina
Original language name
Nonparametric testing of the dependence structure among points-marks-covariates in spatial point patterns
Original language description
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.
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability

Project
<a href="/en/project/GA19-04412S" target="_blank" >GA19-04412S: New approaches to modeling and statistics of random sets</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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