A0369
Title: Burn-in selection in simulating time series
Authors: Chun Yip Yau - Chinese University of Hong Kong (Hong Kong) [presenting]
Abstract: Many time series models are defined in a recursive manner, prohibiting exact simulations. In practice, one appeal to simulating a long time series and discarding a large number of initial simulated observations, known as the burn-in. For autoregressive models where the dependence decays exponentially fast, the choice of the burn-in is not critical. However, it is unclear how to select the burn-in number for long-memory time series where the dependence on the remote past is strong. By combining several samplers with randomized burn-in numbers, a method for exactly simulating the expectation of a statistic computed from a time series is developed. Moreover, with some suitably chosen statistics, the exact simulation method can be applied to quantify the effect of burn-in numbers on the simulated sample. Simulation studies are conducted to provide some practical guidance for burn-in selections.
