Goodness-of-fit test for point processes first-order intensity
Metadatos
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Elsevier
Materia
Point processes First-order intensity Goodness-of-fit
Fecha
2024-02-01Referencia bibliográfica
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]
Patrocinador
Grant PID2020-116587GB-I00 funded by MCIN/AEI/10.13039/501100011033Resumen
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.