Noise inference for ergodic Lévy driven SDE

We study inference for the driving Lévy noise of an ergodic stochastic differential equation (SDE) model, when process is observed at high-frequency and long time drift scale coefficients contain finite-dimensional unknown parameters. By making use Gaussian quasi-likelihood function coefficients, we derive a expansion functionals unit-time residuals, which clarifies some quantitative effect plugging in estimators thereby enabling us to take several procedures driving-noise characteristics into account. also present new classes methods available YUIMA simulation estimation SDE model. highlight flexibility these advances using simulated real data.