0000000000854648
AUTHOR
J. Mateu
Some extensions in space-time LGCP: application to earthquake data
In this paper we aim at studying some extensions of complex space-time models, useful for the description of earthquake data. In particular we want to focus on the Log-Gaussian Cox Process (LGCP, [1]) model estimation approach, with some results on global informal diagnostics. Indeed, in our opinion the use of Cox processes that are natural models for point process phenomena that are environmentally driven could be a new approach for the description of seismic events. These models can be useful in estimating the intensity surface of a spatio-temporal point process, in constructing spatially continuous maps of earthquake risk from spatially discrete data, and in real-time seismic activity su…
Spatio-temporal log-Gaussian Cox processes on eartquake events
In this paper we aim at studying some extensions of complex space-time models, useful for the description of earthquake data. In particular we want to focus on the Log-Gaussian Cox Process (LGCP) model estimation approach, with some results on global informal diagnostics. Indeed, in our opinion the use of Cox processes that are natural models for point process phenomena that are environmentally driven could be a new approach for the description of seismic events. These models can be useful in estimating the intensity surface of a spatio-temporal point process, in constructing spatially continuous maps of earthquake risk from spatially discrete data, and in real-time seismic activity surveil…
Recent advances in space-time statistics with applications to environmental data: An overview
[1] This paper introduces a special section based on general environmental scientific problems, with a particular focus on using atmospheric data. All the papers and authors provide the methodology to study, analyze, predict, and evaluate the spatial-temporal behavior and the complicated spatial-temporal structure of the data. The overall aim is to present up-to-date developments in spatial and spatiotemporal statistics in the field of the atmosphere, to present on-going research, and to discuss important problems to be addressed in the near future.