A maximum likelihood estimation of Lévy-driven stochastic systems for univariate and multivariate time series of observations
单变量与多变量观测时序中 Lévy 驱动随机系统的最大似然估计
Literature is full of inference techniques developed to estimate the parameters of stochastic dynamical systems driven by the well-known Brownian noise. Such diffusion models are often inappropriate models to properly describe the dynamics reflected in many real-world data which are dominated by jump discontinuities of various sizes and frequencies. To account for the presence of jumps, jump-diffusion models are introduced and some inference techniques are developed.…