Title: Expanding Levy-SDE related functions in YUIMA package
Authors: Hiroki Masuda - Kyushu University (Japan) [presenting]
Abstract: Some recent studies are presented on statistical inference for the driving noise of an ergodic Markovian stochastic differential equation (SDE), from the viewpoints of both theory and implementation in R-package YUIMA. The process is supposed to be observed at a high frequency over long-time period. After a brief overview of the Gaussian quasi-likelihood inference, we will present newly expanded Levy-SDE related functions in YUIMA. In particular, we will illustrate some integrated use of the internal functionalities for the quasi-maximum likelihood estimation (qmle) and for handling noise non-Gaussianity (yuima.law-class).