49 citations · 167 across the 32 of their papers we have counts for
5 papers · 1 filter
A new class of spatial covariance functions generated by higher-order kernels
Mohammad Ghorbani, Jorge Mateu
Covariance functions and variograms play a fundamental role in exploratory analysis and statistical modelling of spatial and spatio-temporal datasets. In this paper, we construct a…
Mapping the intensity function of a non-stationary point process in unobserved areas
Edith Gabriel, Francisco J. Rodríguez-Cortes, Jérôme Coville +2
Seismic networks provide data that are used as basis both for public safety decisions and for scientific research. Their configuration affects the data completeness, which in turn,…
Non-stationary spatio-temporal point process modeling for high-resolution COVID-19 data
Zheng Dong, Shixiang Zhu, Yao Xie +2
Most COVID-19 studies commonly report figures of the overall infection at a state- or county-level. This aggregation tends to miss out on fine details of virus propagation. In this…
A non-separable first-order spatio-temporal intensity for events on linear networks: an application to ambulance interventions
Andrea Gilardi, Riccardo Borgoni, Jorge Mateu
The algorithms used for the optimal management of an ambulance fleet require an accurate description of the spatio-temporal evolution of the emergency events. In the last years, se…
Bayesian Effect Selection for Additive Quantile Regression with an Analysis to Air Pollution Thresholds
Nadja Klein, Jorge Mateu
Statistical techniques used in air pollution modelling usually lack the possibility to understand which predictors affect air pollution in which functional form; and are not able t…