8 papers
Consistent community recovery in stochastic block Ornstein-Uhlenbeck processes
Anders Norlyk, Almut E. D. Veraart
We propose the stochastic block Ornstein-Uhlenbeck (SBOU) process, a continuous-time multivariate model in which the drift matrix encodes a latent group structure among its compone…
Edge-indexed network time series with graph Ornstein-Uhlenbeck dynamics
Jiaming Chen, Almut E. D. Veraart
We introduce a class of Lévy-driven graph Ornstein-Uhlenbeck (grOU) models for edge-indexed network time series. The proposed framework extends generalized network autoregressive…
Statistical inference for Levy-driven graph supOU processes: From short- to long-memory in high-dimensional time series
Shreya Mehta, Almut E. D. Veraart
This article introduces Levy-driven graph supOU processes, a parsimonious parametrisation for high-dimensional time series in which dependence between components is governed by a g…
Nonparametric estimation of trawl processes: Theory and applications
Orimar Sauri, Almut E. D. Veraart
Trawl processes belong to the class of continuous-time, strictly stationary, infinitely divisible processes; they are defined as Levy bases evaluated over deterministic trawl sets.…
Simulation-based inference via telescoping ratio estimation for trawl processes
Dan Leonte, Raphaël Huser, Almut E. D. Veraart
The growing availability of large and complex datasets has increased interest in temporal stochastic processes that can capture stylized facts such as marginal skewness, non-Gaussi…
Causal tail coefficient for compound extremes in multivariate time series
Cathy Yin, Adam M. Sykulski, Almut E. D. Veraart
Extreme events are often multivariate in nature. A compound extreme occurs when a combination of variables jointly produces a significant impact, even if individual components are…