activity
20192022
most citedDistributed ARIMA Models for Ultra-long Time Series

80 citations · 110 across the 4 of their papers we have counts for

collaborators

5 papers

stat.ME2022★ 2 cited

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"…

stat.ME2022★ 1 cited

Forecast combinations: an over 50-year review

Xiaoqian Wang, Rob J Hyndman, Feng Li +1

Forecast combinations have flourished remarkably in the forecasting community and, in recent years, have become part of the mainstream of forecasting research and activities. Combi…

stat.AP2020★ 27 cited

Forecasting: theory and practice

Fotios Petropoulos, Daniele Apiletti, Vassilios Assimakopoulos +77

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organ…

stat.AP2020★ 80 cited

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…

stat.ME2019

The uncertainty estimation of feature-based forecast combinations

Xiaoqian Wang, Yanfei Kang, Fotios Petropoulos +1

Forecasting is an indispensable element of operational research (OR) and an important aid to planning. The accurate estimation of the forecast uncertainty facilitates several opera…