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dc.contributor.authorBorrajo, M. I.
dc.contributor.authorGonzález Manteiga, W.
dc.contributor.authorMartínez Miranda, María Dolores 
dc.date.accessioned2024-06-12T09:08:12Z
dc.date.available2024-06-12T09:08:12Z
dc.date.issued2024-02-01
dc.identifier.citationBorrajo, 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.urihttps://hdl.handle.net/10481/92525
dc.description.abstractModelling 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.sponsorshipGrant PID2020-116587GB-I00 funded by MCIN/AEI/10.13039/501100011033es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectPoint processeses_ES
dc.subjectFirst-order intensityes_ES
dc.subjectGoodness-of-fites_ES
dc.titleGoodness-of-fit test for point processes first-order intensityes_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1016/j.csda.2024.107929
dc.type.hasVersionVoRes_ES


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