SB-ETAS: using simulation based inference for scalable, likelihood-free inference for the ETAS model of earthquake occurrences
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Publication:6643206
DOI10.1007/s11222-024-10486-6MaRDI QIDQ6643206
Samuel Stockman, Maximilian J. Werner, Daniel John Lawson
Publication date: 26 November 2024
Published in: Statistics and Computing (Search for Journal in Brave)
Computational methods for problems pertaining to statistics (62-08) Inference from spatial processes (62M30) Non-Markovian processes: estimation (62M09) Bayesian inference (62F15) Seismology (including tsunami modeling), earthquakes (86A15) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)
Cites Work
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- Bayesian inference for Hawkes processes
- The asymptotic behaviour of maximum likelihood estimators for stationary point processes
- Space-time point-process models for earthquake occurrences
- A review of self-exciting spatio-temporal point processes and their applications
- Asymptotic properties of the maximum likelihood estimator for spatio-temporal point processes
- GP-ETAS: semiparametric Bayesian inference for the spatio-temporal epidemic type aftershock sequence model
- Reactive point processes: a new approach to predicting power failures in underground electrical systems
- Diagnostic tools for approximate Bayesian computation using the coverage property
- Semi-automatic selection of summary statistics for ABC model choice
- A Kernel Method for Smoothing Point Process Data
- Estimation of slowly decreasing Hawkes kernels: application to high-frequency order book dynamics
- The frontier of simulation-based inference
- Testing Statistical Hypotheses
- Spectra of some self-exciting and mutually exciting point processes
- Approximation of Bayesian Hawkes process with \texttt{inlabru}
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