This article concerns a perfect simulation algorithm for unmarked and marked Hawkes processes. The usual stratihtforward simulation algorithm suffers from edge effects, whereas our perfect simulation algorithm does not. By viewing Hawkes processes as Poisson cluster processes and using their branching and conditional independence structure, useful approximations of the distribution function for the length of a cluster are derived. This is used to construct upper and lower processes for the perfect simulation algorithm. Examples of applications and empirical results are presented
Point process is a common statistical model used to describe the pattern of event occurrence for man...
The Hawkes process is a self-exciting Poisson point process, characterised by a conditional intensit...
We introduce a broad family of generalised self-exciting point processes with CIR-type intensities, ...
Our objective is to construct a perfect simulation algorithm for unmarked and marked Hawkes processe...
Hawkes processes are important in point process theory and its applications, and simulation of such ...
The usual straightforward simulation algorithm for (marked or unmarked) Hawkes processes suffers fro...
The usual direct method of simulation for cluster processes requires the generation of the parent po...
We introduce a numerically efficient simulation algorithm for Hawkes process with exponentially deca...
This article concerns a simulation algorithm for unmarked and marked Hawkes processes. The algorithm...
AbstractWe present a perfect simulation algorithm for measures that are absolutely continuous with r...
We present a perfect simulation algorithm for measures that are absolutely continuous with respect t...
Hawkes processes are a special class of inhomogenous Poisson processes used to model events exhibiti...
Linear Hawkes processes form a class of branching point processes that is especially relevant to sei...
57 pages. A thesis presented to the Department of Mathematics and the Clark Honors College of the Un...
We derive summary statistics for stationary Hawkes processes which can be considered as spatial vers...
Point process is a common statistical model used to describe the pattern of event occurrence for man...
The Hawkes process is a self-exciting Poisson point process, characterised by a conditional intensit...
We introduce a broad family of generalised self-exciting point processes with CIR-type intensities, ...
Our objective is to construct a perfect simulation algorithm for unmarked and marked Hawkes processe...
Hawkes processes are important in point process theory and its applications, and simulation of such ...
The usual straightforward simulation algorithm for (marked or unmarked) Hawkes processes suffers fro...
The usual direct method of simulation for cluster processes requires the generation of the parent po...
We introduce a numerically efficient simulation algorithm for Hawkes process with exponentially deca...
This article concerns a simulation algorithm for unmarked and marked Hawkes processes. The algorithm...
AbstractWe present a perfect simulation algorithm for measures that are absolutely continuous with r...
We present a perfect simulation algorithm for measures that are absolutely continuous with respect t...
Hawkes processes are a special class of inhomogenous Poisson processes used to model events exhibiti...
Linear Hawkes processes form a class of branching point processes that is especially relevant to sei...
57 pages. A thesis presented to the Department of Mathematics and the Clark Honors College of the Un...
We derive summary statistics for stationary Hawkes processes which can be considered as spatial vers...
Point process is a common statistical model used to describe the pattern of event occurrence for man...
The Hawkes process is a self-exciting Poisson point process, characterised by a conditional intensit...
We introduce a broad family of generalised self-exciting point processes with CIR-type intensities, ...