The webinars will take place on Zoom and a link to the virtual room will be sent out to all those who registered at the registration page.
Speaker: Yaozhong Hu (University of Alberta)
Title: Parameter estimation for threshold Ornstein-Uhlenbeck processes from discrete observations
Abstract: Assuming that a threshold Ornstein-Uhlenbeck process is observed at discrete time instants, we shall present the generalized moment estimators to estimate the parameters. The theoretical basis is the celebrated ergodic theorem. To use this theorem we need to find the explicit form of the invariant measure. With the sampling time step arbitrarily fixed, we prove the strong consistency and asymptotic normality of our estimators as the sample size tends to infinity.
This series of webinars addresses all interested people in probability, stochastic analysis, control, risk evaluation, statistics, with a view towards applications, in particular to renewable energy markets and production. This series brings together the major research themes of the projects STORM, SCROLLER, and SPATUS.