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In this paper we consider multivariate Hawkes processes with baseline hazard and kernel functions that depend on time. This defines a class of locally stationary processes. We discuss estimation of the time-dependent baseline hazard and…

Statistics Theory · Mathematics 2017-07-17 Enno Mammen

We consider the problem of inference for non-stationary time series with heavy-tailed error distribution. Under a time-varying linear process framework we show that there exists a suitable local approximation by a stationary process with…

Statistics Theory · Mathematics 2024-07-09 Fumiya Akashi , Konstantinos Fokianos , Junichi Hirukawa

Multivariate Hawkes processes are a widely used class of self-exciting point processes, but maximum likelihood estimation naively scales as $O(N^2)$ in the number of events. The canonical linear exponential Hawkes process admits a faster…

Machine Learning · Computer Science 2026-05-07 Ahmer Raza , Hudson Smith

We aim to explicitly model the delayed Granger causal effects based on multivariate Hawkes processes. The idea is inspired by the fact that a causal event usually takes some time to exert an effect. Studying this time lag itself is of…

Machine Learning · Computer Science 2023-08-14 Chao Yang , Hengyuan Miao , Shuang Li

We provide probabilistic and computational results on Markovian multivariate Hawkes processes and induced population processes. By applying the Markov property, we characterize in closed form a joint transform, bijective to the probability…

Probability · Mathematics 2025-08-08 R. S. Karim , R. J. A. Laeven , M , M. Mandjes

In this paper, we discuss integer-valued autoregressive time series (INAR), Hawkes point processes, and their interrelationship. Besides presenting structural analogies, we derive a convergence theorem. More specifically, we generalize the…

Probability · Mathematics 2022-08-18 Matthias Kirchner

Hawkes process is a class of simple point processes that is self-exciting and has clustering effect. The intensity of this point process depends on its entire past history. It has wide applications in finance, neuroscience and many other…

Probability · Mathematics 2015-03-18 Lingjiong Zhu

Modelling and forecasting the occurrence of extreme events is especially difficult when the event process is nonstationary, with changes in both the rate at which extremes occur and the magnitude of the extremes when they occur. We approach…

Methodology · Statistics 2026-05-06 Gordon J. Ross , Dean Markwick

Industrial processes generate a massive amount of monitoring data that can be exploited to uncover hidden time losses in the system. This can be used to enhance the accuracy of maintenance policies and increase the effectiveness of the…

Applications · Statistics 2025-08-27 Fernando Miguelez , Josu Doncel , Maria Dolores Ugarte

Critically ill patients in regular wards are vulnerable to unanticipated adverse events which require prompt transfer to the intensive care unit (ICU). To allow for accurate prognosis of deteriorating patients, we develop a novel…

Machine Learning · Computer Science 2017-05-16 Ahmed M. Alaa , Scott Hu , Mihaela van der Schaar

An extension of the Hawkes model where the productivity is variable is considered. In particular, the case is considered where each point may have its own productivity and a simple analytic formula is derived for the maximum likelihood…

Applications · Statistics 2020-03-20 Frederic Paik Schoenberg

We propose a simulation method for multidimensional Hawkes processes based on superposition theory of point processes. This formulation allows us to design efficient simulations for Hawkes processes with differing exponentially decaying…

Machine Learning · Statistics 2018-03-14 Kar Wai Lim , Young Lee , Leif Hanlen , Hongbiao Zhao

Foundational marked temporal point process (MTPP) models, such as the Hawkes process, often use inexpressive model families in order to offer interpretable parameterizations of event data. On the other hand, neural MTPPs models forego this…

Machine Learning · Statistics 2025-11-04 Alex Boyd , Andrew Warrington , Taha Kass-Hout , Parminder Bhatia , Danica Xiao

Locally stationary Hawkes processes have been introduced in order to generalise classical Hawkes processes away from stationarity by allowing for a time-varying second-order structure. This class of self-exciting point processes has…

Statistics Theory · Mathematics 2018-01-31 François Roueff , Rainer Von Sachs

Many time series are effectively generated by a combination of deterministic continuous flows along with discrete jumps sparked by stochastic events. However, we usually do not have the equation of motion describing the flows, or how they…

Machine Learning · Computer Science 2020-01-09 Junteng Jia , Austin R. Benson

Hawkes processes are a popular framework to model the occurrence of sequential events, i.e., occurrence dynamics, in several fields such as social diffusion. In real-world scenarios, the inter-arrival time among events is irregular.…

Machine Learning · Computer Science 2023-05-19 Minju Jo , Seungji Kook , Noseong Park

In the last decade Hawkes processes have received much attention as models for functional connectivity in neural spiking networks and other dynamical systems with a cascade behavior. In this paper we establish a renewal approach for…

Probability · Mathematics 2019-06-11 Mads Bonde Raad

In this paper, we consider the composition of two independent processes : one process corresponds to position and the other one to time. Such processes will be called iterated processes. We first propose an algorithm based on the Euler…

Probability · Mathematics 2017-05-03 Michèle Thieullen , Alexis Vigot

We consider a discrete-time version of a Hawkes process defined as a Poisson auto-regressive process whose parameters depend on the past of the trajectory. We allow these parameters to take on negative values, modelling inhibition. More…

Probability · Mathematics 2024-02-19 Manon Costa , Pascal Maillard , Anthony Muraro

The present paper provides exact mathematical expressions for the high-order moments of spiking activity in a recurrently-connected network of linear Hawkes processes. It extends previous studies that have explored the case of a (linear)…

Neurons and Cognition · Quantitative Biology 2019-12-17 Matthieu Gilson , Jean-Pascal Pfister