報告承辦單位: 數學與統計學院
報告題目: Burn-in selection in simulating time series
報告內容: Many time series models are defined in a recursive manner, which prohibits exact simulations. In practice, one appeals 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, for long-memory time series where the dependence
from the remote past is strong, it is not clear how to select the burn-in number. By combining several samplers with randomized burn-in numbers, we develop a method for exactly simulating the expectation of a statistic computed from a time series. 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. Extensive simulation studies are conducted to provide some practical guidance for burn-in selections.
報告人姓名: Chun Yip Yau
報告人所在單位: Chinese University of Hong Kong
報告人職稱:教授
報告時間:2022年12月5日, 星期一，下午3:00-4:00
在線報告:騰訊會議號碼：236-568-028
報告人簡介：Chun Yip Yau is currently a professor in Department of Statistics, Chinese University of Hong Kong. He obtained his PhD from Columbia University in 2010. His research interest includes time series, change-point analysis, spatial statistics and extreme value theory.