Perfect simulation of Hawkes processes
نویسندگان
چکیده
منابع مشابه
Perfect Simulation of Hawkes Processes
This article concerns a perfect simulation algorithm for unmarked and marked Hawkes processes. The usual straightforward 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...
متن کاملApproximate Simulation of Hawkes Processes
This article concerns a simulation algorithm for unmarked and marked Hawkes processes. The algorithm suffers from edge effects but is much faster than the perfect simulation algorithm introduced in our previous work [12]. We derive various useful measures for the error committed when using the algorithm, and we discuss various empirical results for the algorithm compared with perfect simulations.
متن کاملSimulation , Estimation and Applications of Hawkes Processes
Hawkes processes are a particularly interesting class of stochastic processes that were introduced in the early seventies by A. G. Hawkes, notably to model the occurrence of seismic events. Since then they have been applied in diverse areas, from earthquake modeling to financial analysis. The processes themselves are characterized by a stochastic intensity vector, which represents the condition...
متن کاملJesper Møller and Jacob G . Rasmussen : Perfect Simulation of Hawkes Processes
This article concerns a perfect simulation algorithm for unmarked and marked Hawkes processes. The usual straightforward 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...
متن کاملIsotonic Hawkes Processes
0 g⇤(w⇤ ·xt)dt = P j2Si aijg ⇤ (w⇤ ·xj). Set y⇤ i = g ⇤ (w⇤ ·xi) to be the expected value of each yi. Let ̄ Ni be the expected value of Ni. Then we have ̄ Ni = P j2Si aijy ⇤ j . Clearly we do not have access to ̄ Ni. However, consider a hypothetical call to the algorithm with input {(xi, ̄ Ni)}i=1 and suppose it returns ḡk. In this case, we define ȳk i = ḡk(w̄k · xi). Next we begin the proof and int...
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ژورنال
عنوان ژورنال: Advances in Applied Probability
سال: 2005
ISSN: 0001-8678,1475-6064
DOI: 10.1239/aap/1127483739