Hanlin Shang

Stopping time detection in functional time series: An application to Wood industry

We study a functional time series, in the form of near infrared (NIR) spectroscopy curves, for determining phenolic glue curing of wood panels in an automated process environment. We propose a forecasting method for estimating the stopping time in a functional time series. The method is based on iterative forward and backward integrated squared forecasting errors of the holdout functional time series. Based on two time series of the forecast errors, we apply a structure break procedure for univariate time series to identify the stopping time. (Joint work with Jiguo Cao and Peijun Sang)

 

Bio: Han Lin Shang is an Associate Professor of Statistics at the Research School of Finance, Actuarial Studies and Statistics, Australian National University. His research interest include actuarial studies, computational statistics, demographic forecasting and empirical finance. He is serving as an associate editor for Journal of Computational and Graphical Statistics and Australian & New Zealand Journal of Statistics