Add to ORKGA simplified stochastic model for earthquake occurrence focusing on the spatio-temporal interactions between earthquakes is presented. The model is a marked point process model in which each earthquake is represented by its magnitude and coordinates in space and time. The model incorporates the occurrence of aftershocks as well as the build-up and subsequent release of strain. The parameters of the model are estimated from a maximum likelihood calculation
Earthquakes are regarded as the realizations of a point process modeled by a generalized Poisson di...
[1] Earthquakes and the faults upon which they occur interact over a wide range of spatial and tempo...
Methods of examining the fit of multi-dimensional point process models using residual analysis are p...
International audienceA simplified stochastic model for earthquake occurrence focusing on the spatio...
Two new different stochastic models for earthquake occurrence are discussed. Both models are focusin...
Two new different stochastic models for earthquake occurrence are discussed. Both models are focusin...
The main task in earthquake prediction is to develop statistical models for analyzing the observatio...
Online Material: Sensitivity to scaling of the d-parameter and to inhomogeneous background activity,...
Point processes have long been used as an effective modeling technique in the forecasting of earthqu...
International audienceOccurrence of successive earthquake events in space is analysed by means of se...
[1] Assuming that earthquakes are the realization of a stochastic point process and that the magnitu...
Assuming that earthquakes are the realization of a stochastic point process and that themagnitude di...
Stochastic modelling of sequences of seismic events in order to evaluate the long-term hazard is typ...
A stochastic model is presented for estimating probabilities of exceeding site ground motions due to...
Two widely noted features of earthquake generation are the following: - earthquakes tend to occur in...
Earthquakes are regarded as the realizations of a point process modeled by a generalized Poisson di...
[1] Earthquakes and the faults upon which they occur interact over a wide range of spatial and tempo...
Methods of examining the fit of multi-dimensional point process models using residual analysis are p...
International audienceA simplified stochastic model for earthquake occurrence focusing on the spatio...
Two new different stochastic models for earthquake occurrence are discussed. Both models are focusin...
Two new different stochastic models for earthquake occurrence are discussed. Both models are focusin...
The main task in earthquake prediction is to develop statistical models for analyzing the observatio...
Online Material: Sensitivity to scaling of the d-parameter and to inhomogeneous background activity,...
Point processes have long been used as an effective modeling technique in the forecasting of earthqu...
International audienceOccurrence of successive earthquake events in space is analysed by means of se...
[1] Assuming that earthquakes are the realization of a stochastic point process and that the magnitu...
Assuming that earthquakes are the realization of a stochastic point process and that themagnitude di...
Stochastic modelling of sequences of seismic events in order to evaluate the long-term hazard is typ...
A stochastic model is presented for estimating probabilities of exceeding site ground motions due to...
Two widely noted features of earthquake generation are the following: - earthquakes tend to occur in...
Earthquakes are regarded as the realizations of a point process modeled by a generalized Poisson di...
[1] Earthquakes and the faults upon which they occur interact over a wide range of spatial and tempo...
Methods of examining the fit of multi-dimensional point process models using residual analysis are p...