2 papers
math.ST2026
Sparse Estimation for High-Dimensional Lévy-driven Ornstein--Uhlenbeck Processes from Discrete Observations
Niklas Dexheimer, Natalia Jeszka
We study high-dimensional drift estimation for Lévy-driven Ornstein--Uhlenbeck processes based on discrete observations. Assuming sparsity of the drift matrix, we analyze Lasso and…
math.ST2022
On Lasso and Slope drift estimators for Lévy-driven Ornstein--Uhlenbeck processes
Niklas Dexheimer, Claudia Strauch
We investigate the problem of estimating the drift parameter of a high-dimensional Lévy-driven Ornstein--Uhlenbeck process under sparsity constraints. It is shown that both Lasso a…