5 papers
Optimal starting point for time series forecasting
Yiming Zhong, Yinuo Ren, Guangyao Cao +2
Recent advances on time series forecasting mainly focus on improving the forecasting models themselves. However, when the time series data suffer from potential structural breaks o…
Grid Point Approximation for Distributed Nonparametric Smoothing and Prediction
Yuan Gao, Rui Pan, Feng Li +2
Kernel smoothing is a widely used nonparametric method in modern statistical analysis. The problem of efficiently conducting kernel smoothing for a massive dataset on a distributed…
Another look at forecast trimming for combinations: robustness, accuracy and diversity
Xiaoqian Wang, Yanfei Kang, Feng Li
Forecast combination is widely recognized as a preferred strategy over forecast selection due to its ability to mitigate the uncertainty associated with identifying a single "best"…
Distributed ARIMA Models for Ultra-long Time Series
Xiaoqian Wang, Yanfei Kang, Rob J Hyndman +1
Providing forecasts for ultra-long time series plays a vital role in various activities, such as investment decisions, industrial production arrangements, and farm management. This…
Discrete forecast reconciliation
Bohan Zhang, Anastasios Panagiotelis, Yanfei Kang
This paper presents a formal framework and proposes algorithms to extend forecast reconciliation to discrete-valued data to extend forecast reconciliation to discrete-valued data,…