期刊
INTERNATIONAL STATISTICAL REVIEW
卷 90, 期 3, 页码 592-621出版社
WILEY
DOI: 10.1111/insr.12503
关键词
Covariate; hypothesis testing; independence; marked point process; nonparametric inference
资金
- Grant Agency of the Czech Republic [19-04412S]
- Ministerio de Ciencia e Innovacion [MTM2016-78917-R]
- Generalitat Valenciana [AICO/2019/198]
- Universitat Jaume I [UJI-B2018-04]
We investigate a testing method for the hypothesis of independence between a covariate and the marks in a marked point process. We propose to study the complete dependence structure in the triangle points-marks-covariates together and use a new variance correction approach for the tests. Simulation studies and real applications are conducted to demonstrate the performance of the methods.
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.
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