1 citations · 3 across the 6 of their papers we have counts for
5 papers · 1 filter
Likelihood-based inference and forecasting for trawl processes: a stochastic optimization approach
Dan Leonte, Almut E. D. Veraart
We consider trawl processes, which are stationary and infinitely divisible stochastic processes and can describe a wide range of statistical properties, such as heavy tails and lon…
Estimation and Inference for Multivariate Continuous-time Autoregressive Processes
Lorenzo Lucchese, Mikko S. Pakkanen, Almut E. D. Veraart
The aim of this paper is to develop estimation and inference methods for the drift parameters of multivariate Lévy-driven continuous-time autoregressive processes of order $p\in\ma…
Simulation methods and error analysis for trawl processes and ambit fields
Dan Leonte, Almut E. D. Veraart
Trawl processes are continuous-time, stationary and infinitely divisible processes which can describe a wide range of possible serial correlation patterns in data. In this paper, w…
Modelling, simulation and inference for multivariate time series of counts
Almut E. D. Veraart
This article presents a new continuous-time modelling framework for multivariate time series of counts which have an infinitely divisible marginal distribution. The model is based…
A Lévy-driven rainfall model with applications to futures pricing
Ragnhild C. Noven, Almut E. D. Veraart, Axel Gandy
We propose a parsimonious stochastic model for characterising the distributional and temporal properties of rainfall. The model is based on an integrated Ornstein-Uhlenbeck process…