Stochastic smoothing of point processes for wildlife-vehicle collisions on road networks (Epub ahead of print)
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Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7037
comunitat-uji-handle3:10234/8635
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INVESTIGACIONMetadata
Title
Stochastic smoothing of point processes for wildlife-vehicle collisions on road networks (Epub ahead of print)Date
2021-09-04Publisher
SpringerISSN
1436-3240; 1436-3259Type
info:eu-repo/semantics/articlePublisher version
https://link.springer.com/content/pdf/10.1007/s00477-021-02072-3.pdfVersion
info:eu-repo/semantics/publishedVersionSubject
Abstract
Wildlife-vehicle collisions on road networks represent a natural problem between human populations and the environment, that affects wildlife management and raise a risk to the life and safety of car drivers. We propose ... [+]
Wildlife-vehicle collisions on road networks represent a natural problem between human populations and the environment, that affects wildlife management and raise a risk to the life and safety of car drivers. We propose a statistically principled method for kernel smoothing of point pattern data on a linear network when the first-order intensity depends on covariates. In particular, we present a consistent kernel estimator for the first-order intensity function that uses a convenient relationship between the intensity and the density of events location over the network, which also exploits the theoretical relationship between the original point process on the network and its transformed process through the covariate. We derive the asymptotic bias and variance of the estimator, and adapt some data-driven bandwidth selectors to estimate the optimal bandwidth. The performance of the estimator is analysed through a simulation study under inhomogeneous scenarios. We present a real data analysis on wildlife-vehicle collisions in a region of North-East of Spain. [-]
Is part of
Stochastic Environmental Research and Risk Assessment, 2021Project code
MTM-2016-78917-R | UJI-B2018-04
Project title or grant
Nuevas familias de procesos estocásticos espacio-temporales que unifican geoestadística y patrones puntuales, modelización, estimación, predicción sobre networks y trayectoria | Procesos puntuales espaciales y espacio-temporales sobre redes. Características de segundo orden y modelos probabilísticos
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info:eu-repo/semantics/openAccess
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