1 citations · 1 across the 2 of their papers we have counts for
4 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…
Likelihood inference of the non-stationary Hawkes process with non-exponential kernel
Tsz-Kit Jeffrey Kwan, Feng Chen, William Dunsmuir
The Hawkes process is a popular point process model for event sequences that exhibit temporal clustering. The intensity process of a Hawkes process consists of two components, 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…