2026-05-30T08:45:36Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/302902026-02-03T11:08:09Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Frías, María P.
author
Torres-Signes, Antoni
author
Ruiz-Medina, María D.
2024-02-09T12:04:57Z
2024-02-09T12:04:57Z
2023-02-14
Frías, M.P., Torres, A. & Ruiz-Medina, M.D. Point pattern analysis and classification on compact two-point homogeneous spaces evolving time. Stoch Environ Res Risk Assess 37, 2145–2158 (2023).
https://hdl.handle.net/10630/30290
10.1007/s00477-023-02384-6
This paper introduces a new modeling framework for the statistical analysis of point patterns on a manifold Md; defined by a connected and compact two-point homogeneous space, including the special case of the sphere. The presented approach is based on temporal Cox processes driven by a L2(Md)-valued log-intensity. Different aggregation schemes on the manifold of the spatiotemporal point-referenced data are implemented in terms of the time-varying discrete Jacobi polynomial transform of the log-risk process. The n-dimensional microscale point pattern evolution in time at different manifold spatial scales is then characterized from such a transform. The simulation study undertaken illustrates the construction of spherical point process models displaying aggregation at low Legendre polynomial transform frequencies (large scale), while regularity is observed at high frequencies (small scale). K-function analysis supports these results under temporal short, intermediate and long range dependence of the log-risk process.
eng
Análisis multivariante
Point pattern analysis and classification on compact two-point homogeneous spaces evolving time.
journal article
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URL
https://riuma.uma.es/bitstreams/4bfa5aa8-9f0c-480d-b278-14664a84c74e/download
File
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c048622bac4d72cb55fb01f720cbcc9c
2268917
application/pdf
SERRA-2023.pdf