Search results for "EtasFLP"

showing 5 items of 5 documents

Space-time Point Processes semi-parametric estimation with predictive measure information

2014

In this paper, we provide a method to estimate the space-time intensity of a branching-type point process by mixing nonparametric and parametric approaches. The method accounts simultaneously for the estimation of the different model components, applying a forward predictive likelihood estimation approach to semi-parametric models.

Point Process.etasFLPNonparametric EstimationForward Predictive Likelihood
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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…

Statistics and ProbabilityComputer scienceSpace timeR packageProbability and statisticsManagement Monitoring Policy and LawSpace-time point processePoint processSemiparametric modelTerm (time)ETAS modelComputers in Earth ScienceComponent (UML)StatisticsCode (cryptography)Computers in Earth SciencesAlgorithmEtasFLPParametric statistics
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Mixed Non-Parametric and Parametric Estimation Techniques in R Package etasFLP for Earthquakes’ Description

2017

etasFLP is an R package which fits an epidemic type aftershock sequence (ETAS) model to an earthquake catalog; non-parametric background seismicity can be estimated through a forward predictive likelihood approach, while parametric components of triggered seismicity are estimated through maximum likelihood; estimation steps are alternated until convergence is obtained and for each event the probability of being a background event is estimated. The package includes options which allow its wide use. Methods for plot, summary and profile are defined for the main output class object. The paper provides examples of the package's use with description of the underlying R and Fortran routines.

Statistics and ProbabilityEarthquakeComputer scienceFortranFortranInduced seismicity010502 geochemistry & geophysicscomputer.software_genre01 natural sciencesPlot (graphics)Point processPhysics::GeophysicsPoint proce010104 statistics & probabilityetasFLP; R; Fortran; point process; ETAS; earthquakesETAS0101 mathematicsearthquakeslcsh:Statisticslcsh:HA1-4737AftershockEtasFLPpoint process0105 earth and related environmental sciencesEvent (probability theory)Parametric statisticscomputer.programming_languageNonparametric statisticsRetasFLP R Fortran point process ETAS earthquakes.Data miningStatistics Probability and UncertaintySettore SECS-S/01 - StatisticacomputerAlgorithmSoftware
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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…

Statistics and ProbabilityNonparametric statisticsManagement Monitoring Policy and LawInduced seismicityGeodesyPoint processPhysics::GeophysicsLatitudeSpace-time point processes ETAS model etasFLP R packagePredictive likelihoodStatisticsSensitivity (control systems)Computers in Earth SciencesAftershockGeologyParametric statistics
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Space-Time Forecasting of Seismic Events in Chile

2017

The aim of this work is to study the seismicity in Chile using the ETAS (epidemic type aftershock sequences) space‐time approach. The proposed ETAS model is estimated using a semi‐parametric technique taking into account the parametric and nonparametric components corresponding to the triggered and background seismicity, respectively. The model is then used to predict the temporal and spatial intensity of events for some areas of Chile where recent large earthquakes (with magnitude greater than 8.0 M) occurred.

space‐time point processes conditional intensity function ETAS model etasFLP(R package) forecastSpace timeforecsting Chile esrthquakesSettore SECS-S/01 - StatisticaGeologySeismology
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