1 citations · 1 across the 5 of their papers we have counts for
5 papers
Neural Networks for Parameter Estimation of the Discretely Observed Hawkes Process
Jason J. Lambe, Feng Chen, Tom Stindl +1
When the sample path of a Hawkes process is observed discretely, such that only the total event counts in disjoint time intervals are known, the likelihood function becomes intract…
Parametric inference for the discretely observed multivariate Hawkes process using particle Markov Chain Monte Carlo
Jason J. Lambe, Feng Chen, Tom Stindl +1
The multivariate Hawkes process (MHP) is a useful statistical model for analysing multidimensional event time sequences that exhibit self-excitation and cross-excitation. When the…
Estimating the Hawkes process from a discretely observed sample path
Feng Chen, Jeffrey Kwan, Tom Stindl
The Hawkes process is a widely used model in many areas, such as finance, seismology, neuroscience, epidemiology, and social sciences. Estimation of the Hawkes process from continu…
Stochastic declustering of earthquakes with the spatiotemporal RETAS model
Tom Stindl, Feng Chen
Epidemic-Type Aftershock Sequence (ETAS) models are point processes that have found prominence in seismological modeling. Its success has led to the development of a number of diff…
Spatiotemporal ETAS model with a renewal main-shock arrival process
Tom Stindl, Feng Chen
This article proposes a spatiotemporal point process model that enhances the classical Epidemic-Type Aftershock Sequence (ETAS) model by incorporating a renewal main-shock arrival…