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 routine
This paper describes the package PtProcess which uses the R statistical language. The package provid...
An estimation approach for the semi-parametric intensity function of a particular space-time point ...
The paper proposes a stochastic process that improves the assessment of events in space and time, c...
etasFLP is an R package which fits an epidemic type aftershock sequence (ETAS) model to an earthquak...
etasFLP is an R package which fits an epidemic type aftershock sequence (ETAS) model to an earthquak...
Predictive) and ML estimation of non-parametric and parametric components of the ETAS model for eart...
An estimation approach for the semi-param-etric intensity function of a class of space-time point p...
The epidemic-type aftershock sequence (ETAS) model is the most widely used statistical model to desc...
The spatio-temporal epidemic type aftershock sequence (ETAS) model is widely used to describe the se...
The seismicity in Chile is estimated using an ETAS (Epidemic Type Aftershock sequences) space-time p...
This paper investigates the basic properties of the recent shallow seismicity in Italy through stoch...
Epidemic-type aftershock sequence (ETAS) point process is a common model for the occurrence of earth...
This study investigates the basic properties of the recent shallow seismicity in Italy, through stoc...
Abstract We present a non-stationary epidemic-type aftershock sequence (ETAS) model in which the usu...
Branching processes provide an accurate description of earthquake occurrence in the short term (day...
This paper describes the package PtProcess which uses the R statistical language. The package provid...
An estimation approach for the semi-parametric intensity function of a particular space-time point ...
The paper proposes a stochastic process that improves the assessment of events in space and time, c...
etasFLP is an R package which fits an epidemic type aftershock sequence (ETAS) model to an earthquak...
etasFLP is an R package which fits an epidemic type aftershock sequence (ETAS) model to an earthquak...
Predictive) and ML estimation of non-parametric and parametric components of the ETAS model for eart...
An estimation approach for the semi-param-etric intensity function of a class of space-time point p...
The epidemic-type aftershock sequence (ETAS) model is the most widely used statistical model to desc...
The spatio-temporal epidemic type aftershock sequence (ETAS) model is widely used to describe the se...
The seismicity in Chile is estimated using an ETAS (Epidemic Type Aftershock sequences) space-time p...
This paper investigates the basic properties of the recent shallow seismicity in Italy through stoch...
Epidemic-type aftershock sequence (ETAS) point process is a common model for the occurrence of earth...
This study investigates the basic properties of the recent shallow seismicity in Italy, through stoc...
Abstract We present a non-stationary epidemic-type aftershock sequence (ETAS) model in which the usu...
Branching processes provide an accurate description of earthquake occurrence in the short term (day...
This paper describes the package PtProcess which uses the R statistical language. The package provid...
An estimation approach for the semi-parametric intensity function of a particular space-time point ...
The paper proposes a stochastic process that improves the assessment of events in space and time, c...