Sparse Estimation for High-Dimensional Lévy-driven Ornstein--Uhlenbeck Processes from Discrete Observations
离散观测下高维Lévy驱动OU过程的稀疏估计
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 Slope estimators constructed from approximate likelihoods and derive sharp nonasymptotic oracle inequalities. Our bounds disentangle the contributions of discretization error and stochastic fluctuations, and establish minimax optimal convergence rates under suitable choices of tuning parameters in…