Nonparametric testing of the dependence structure among points-marks-covariates in spatial point patterns
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Otros documentos de la autoría: Mateu, Jorge; Mrkvicka, Tomas; Dvořák, Jiří; González, Jonatan A.
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Título
Nonparametric testing of the dependence structure among points-marks-covariates in spatial point patternsFecha de publicación
2022-05-16Editor
John Wiley & SonsCita bibliográfica
Dvořák, J., Mrkvička, T., Mateu, J., & González, J. A. (2022). Nonparametric Testing of the Dependence Structure Among Points–Marks–Covariates in Spatial Point Patterns. International Statistical Review.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://onlinelibrary.wiley.com/doi/epdf/10.1111/insr.12503Versión
info:eu-repo/semantics/submittedVersionPalabras clave / Materias
Resumen
We investigate testing of the hypothesis of independence between a covariate and the marks in amarked point process. It would be rather straightforward if the (unmarked) point process wereindependent of the covariate ... [+]
We investigate testing of the hypothesis of independence between a covariate and the marks in amarked point process. It would be rather straightforward if the (unmarked) point process wereindependent of the covariate and the marks. In practice, however, such an assumption isquestionable and possible dependence between the point process and the covariate or the marksmay lead to incorrect conclusions. Therefore, we propose to investigate the complete dependencestructure in the triangle points–marks–covariates together. We take advantage of the recentdevelopment of the nonparametric random shift methods, namely, the new variance correctionapproach, and propose tests of the null hypothesis of independence between the marks and thecovariate and between the points and the covariate. We present a detailed simulation study showingthe performance of the methods and provide two theorems establishing the appropriate form of thecorrection factors for the variance correction. Finally, we illustrate the use of the proposed methodsin two real applications. [-]
Publicado en
International Statistical Review(2022) doi: 10.1111/insr.12503Entidad financiadora
Ministerio de Ciencia, Innovación y Universidades (Spain) | Generalitat Valenciana | Universitat Jaume I | Grant Agency of the Czech Republic
Código del proyecto o subvención
9-04412S | AICO/2019/198 | UJI-B2018-04 | 19-04412S
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© 2022 International Statistical Institute
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