Including covariates in a space-time point process with application to seismicity
Giada Adelfio, Marcello Chiodi
Abstract
Abstract The 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.
Topics & Concepts
CovariatePoint processInduced seismicityProcess (computing)Computer scienceEconometricsComponent (thermodynamics)Space timePoint (geometry)SpecificationStatisticsData miningMathematicsSeismologyGeologyEngineeringPhysicsOperating systemChemical engineeringGeometryThermodynamicsPoint processes and geometric inequalitiesSpatial and Panel Data AnalysisData-Driven Disease Surveillance