Adaptively Combined Forecasting for Discrete Responses
Dr Xinyu Zhang, Academy of Mathematics and Systems Science, Chinese Academy of Sciences
9th Aug 2012 01:00 pm - Room 489 Merewether Building (H04)
Adaptive combining is generally desirable for forecasts. In this paper, we propose an adaptively combined forecasting method for discrete response time series data. We demonstrate in theory that the proposed forecast is of the desired adaptation with respect to the widely used squared risk and other significant risk functions under mild conditions. Furthermore, we study the adaptation of the proposed forecasting method with a model screening step that is often useful in applications. Our simulation study evidently illustrates the superiority of the proposed approach, with two real-world data examples further demonstrated.