Search results for "Space-time point processe"

Including covariates in a space-time point process with application to seismicity

2020

AbstractThe paper proposes a spatio-temporal process that improves the assessment of events in space and time, considering a contagion model (branching process) within a regression-like framework to take covariates into account. The proposed approach develops the forward likelihood for prediction method for estimating the ETAS model, including covariates in the model specification of the epidemic component. A simulation study is carried out for analysing the misspecification model effect under several scenarios. Also an application to the Italian seismic catalogue is reported, together with the reference to the developed R package.

FLP estimation of semi-parametric models for space-time point processes and diagnostic tools

2015

Abstract The conditional intensity function of a space–time branching model is defined by the sum of two main components: the long-run term intensity and short-run term one. Their simultaneous estimation is a complex issue that usually requires the use of hard computational techniques. This paper deals with a new mixed estimation approach for a particular space–time branching model, the Epidemic Type Aftershock Sequence model. This approach uses a simultaneous estimation of the different model components, alternating a parametric step for estimating the induced component by Maximum Likelihood and a non-parametric estimation step, for the background intensity, by FLP (Forward Predictive Like…

Hybrid kernel estimates of space-time earthquake occurrence rates using the Etas model

2010

The following steps are suggested for smoothing the occurrence patterns in a clustered space–time process, in particular the data from an earthquake catalogue. First, the original data is fitted by a temporal version of the ETAS model, and the occurrence times are transformed by using the cumulative form of the fitted ETAS model. Then the transformed data (transformed times and original locations) is smoothed by a space–time kernel with bandwidth obtained by optimizing a naive likelihood cross-validation. Finally, the estimated intensity for the original data is obtained by back-transforming the estimated intensity for the transformed data. This technique is used to estimate the intensity f…

Windowed Etas Models With Application To The Chilean Seismic Catalogs

2015

Abstract The seismicity in Chile is estimated using an ETAS (Epidemic Type Aftershock sequences) space–time point process through a semi-parametric technique to account for the estimation of parametric and nonparametric components simultaneously. The two components account for triggered and background seismicity respectively, and are estimated by alternating a ML estimation for the parametric part and a forward predictive likelihood technique for the nonparametric one. Given the geographic and seismological characteristics of Chile, the sensitivity of the technique with respect to different geographical areas is examined in overlapping successive windows with varying latitude. A different b…

Nonparametric intensity estimation in space-time point processes and application to seismological problems

2008

Financial contagion through space-time point processes

2020

AbstractWe propose to study the dynamics of financial contagion by means of a class of point process models employed in the modeling of seismic contagion. The proposal extends network models, recently introduced to model financial contagion, in a space-time point process perspective. The extension helps to improve the assessment of credit risk of an institution, taking into account contagion spillover effects.

Some extensions in space-time LGCP: application to earthquake data

2017

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…