Granger causality: A review and recent advances
Introduced more than a half-century ago, Granger causality has become a popular tool for
analyzing time series data in many application domains, from economics and finance to …
analyzing time series data in many application domains, from economics and finance to …
Joint structural break detection and parameter estimation in high-dimensional nonstationary VAR models
Assuming stationarity is unrealistic in many time series applications. A more realistic
alternative is to assume piecewise stationarity, where the model can change at potentially …
alternative is to assume piecewise stationarity, where the model can change at potentially …
Nonparametric Bayesian estimation for multivariate Hawkes processes
This paper studies nonparametric estimation of parameters of multivariate Hawkes
processes. We consider the Bayesian setting and derive posterior concentration rates. First …
processes. We consider the Bayesian setting and derive posterior concentration rates. First …
Bayesian estimation of nonlinear Hawkes processes
The supplementary material contains ten sections and includes proofs and additional
results, notably the proofs of Proposition 2.3, Proposition 2.5, Proposition 3.5, Corollary 3.8 …
results, notably the proofs of Proposition 2.3, Proposition 2.5, Proposition 3.5, Corollary 3.8 …
Learning Network-Structured Dependence From Non-Stationary Multivariate Point Process Data
M Gao, C Zhang, J Zhou - IEEE Transactions on Information …, 2024 - ieeexplore.ieee.org
Learning the sparse network-structured dependence among nodes from multivariate point
process data has wide applications in information transmission, social science, and …
process data has wide applications in information transmission, social science, and …
Neuronal network inference and membrane potential model using multivariate Hawkes processes
Background In this work, we propose to catch the complexity of the membrane potential's
dynamic of a motoneuron between its spikes, taking into account the spikes from other …
dynamic of a motoneuron between its spikes, taking into account the spikes from other …
Numerical method for means of linear Hawkes processes
Z Li, L Cui - Communications in Statistics-Theory and Methods, 2020 - Taylor & Francis
Linear Hawkes processes are widely used in many fields and means are the basic and
critical information of them. However, there is little research on linear Hawkes processes' …
critical information of them. However, there is little research on linear Hawkes processes' …
Hawkesian graphical event models
Graphical event models (GEMs) provide a framework for graphical representation of
multivariate point processes. We propose a class of GEMs named Hawkesian graphical …
multivariate point processes. We propose a class of GEMs named Hawkesian graphical …
PCA for Point Processes
We introduce a novel statistical framework for the analysis of replicated point processes that
allows for the study of point pattern variability at a population level. By treating point process …
allows for the study of point pattern variability at a population level. By treating point process …
Regularised Spectral Estimation for High Dimensional Point Processes
Advances in modern technology have enabled the simultaneous recording of neural spiking
activity, which statistically can be represented by a multivariate point process. We …
activity, which statistically can be represented by a multivariate point process. We …