Directional analysis for point patterns on linear networks
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Título
Directional analysis for point patterns on linear networksFecha de publicación
2020Editor
WileyISSN
2049-1573Cita bibliográfica
Moradi M., J. Mateu, and C. Comas (2020), Directional analysis for point patterns on linear networks , Stat, 2020;00:1–11Tipo de documento
info:eu-repo/semantics/articleVersión
info:eu-repo/semantics/acceptedVersionPalabras clave / Materias
Resumen
Statistical analysis of point processes often assumes that the underlying process is isotropic
in the sense that its distribution is invariant under rotation. For point processes on R2
,
some tests based on the K- ... [+]
Statistical analysis of point processes often assumes that the underlying process is isotropic
in the sense that its distribution is invariant under rotation. For point processes on R2
,
some tests based on the K- and nearest neighbour orientation functions have been proposed
to check such an assumption. However, anisotropy and directional analysis need proper
caution when dealing with point processes on linear networks, as the implicit geometry of
the network forces particular directions that the points of the pattern have to necessarily
meet. In this paper, we adapt such tests to the case of linear networks, and discuss how to
use them to detect particular directional preferences, even at some angles that are different
from the main angles imposed by the network. Through a simulation study, we check the
performance of our proposals under different settings, over a linear network and a dendrite
tree, showing that they are able to precisely detect the directional preferences of the points
in the pattern, regardless the type of spatial interaction and the geometry of the network.
We use our tests to highlight the directional preferences in the spatial distribution of traffic
accidents in Barcelona (Spain) during 2019, and in Medellin (Colombia), during 2016. [-]
Publicado en
Estado, 2020;00:1–11Entidad financiadora
Generalitat Valenciana | Spanish Ministry of Science | Universitat Jaume I
Código del proyecto o subvención
AICO/2019/198 | MTM2017-86767-R | PID2019-107392RB-I00 | UJI-B2018-04
Derechos de acceso
© 2020 John Wiley & Sons, Ltd.
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info:eu-repo/semantics/openAccess
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info:eu-repo/semantics/openAccess
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