RT Journal Article
T1 Spatial Cox processes in an infinite-dimensional framework
A1 Frías, María P.
A1 Torres-Signes, Antoni
A1 Ruiz-Medina, María D.
A1 Mateu, Jorge
K1 Medicina - Modelos matemáticos
AB We introduce a new class of spatial Cox processes driven by a Hilbert-valued random log-intensity. We adopt a parametric framework in the spectral domain, to estimate its spatial functional correlation structure. Specifically, we consider a spectral functional, approach based on the periodogram operator, inspired on Whittle estimation methodology. Strong consistency of the parametric estimator is proved in the linear case. We illustrate this property in a simulation study under a Gaussian first-order Spatial Autoregressive Hilbertian scenario for the log-intensity model. Our method is applied to the spatial functional prediction of respiratory disease mortality in the Spanish Iberian Peninsula, in the period 1980–2015.
YR 2022
FD 2022
LK https://hdl.handle.net/10630/30282
UL https://hdl.handle.net/10630/30282
LA eng
NO Frías, M.P., Torres-Signes, A., Ruiz-Medina, M.D. et al. Spatial Cox processes in an infinite-dimensional framework. TEST 31, 175–203 (2022). https://doi.org/10.1007/s11749-021-00773-z
NO This work has been supported in part by projects PGC2018-099549-B-I00,MTM2016-78917-R, and PID2019-107392RB-100 of the Ministerio de Ciencia, Innovación y Universidades, Spain (co-funded with FEDER funds), and ERDF Operational Programme 2014-2020 and the Economy and Knowledge Council of the Regional Government of Andalusia, Spain (A-FQM-345-UGR18).
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026