dc.contributor.author | Borrajo, M. I. | |
dc.contributor.author | González Manteiga, W. | |
dc.contributor.author | Martínez Miranda, María Dolores | |
dc.date.accessioned | 2024-06-12T09:08:12Z | |
dc.date.available | 2024-06-12T09:08:12Z | |
dc.date.issued | 2024-02-01 | |
dc.identifier.citation | Borrajo, M. I., W. González-Manteiga, and M. D. Martínez-Miranda. Goodness-of-fit test for point processes first-order intensity. Computational Statistics and Data Analysis 194 (2024) 107929 [10.1016/j.csda.2024.107929] | es_ES |
dc.identifier.uri | https://hdl.handle.net/10481/92525 | |
dc.description.abstract | Modelling the first-order intensity function is one of the main aims in point process theory.
An appropriate model describes the first-order intensity as a nonparametric function of spatial
covariates. A formal testing procedure is presented to assess the goodness-of-fit of this model,
assuming an inhomogeneous Poisson point process. The test is based on a quadratic distance
between two kernel intensity estimators. The asymptotic normality of the test statistic is proved
and a bootstrap procedure to approximate its distribution is suggested. The proposal is illustrated
with two applications to real data sets, and an extensive simulation study to evaluate its finitesample
performance. | es_ES |
dc.description.sponsorship | Grant PID2020-116587GB-I00 funded by MCIN/AEI/10.13039/501100011033 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Point processes | es_ES |
dc.subject | First-order intensity | es_ES |
dc.subject | Goodness-of-fit | es_ES |
dc.title | Goodness-of-fit test for point processes first-order intensity | es_ES |
dc.type | journal article | es_ES |
dc.rights.accessRights | open access | es_ES |
dc.identifier.doi | 10.1016/j.csda.2024.107929 | |
dc.type.hasVersion | VoR | es_ES |