99 citations · 312 across the 30 of their papers we have counts for
5 papers · 1 filter
Machine learning applications in time series hierarchical forecasting
Mahdi Abolghasemi, Rob J Hyndman, Garth Tarr +1
Hierarchical forecasting (HF) is needed in many situations in the supply chain (SC) because managers often need different levels of forecasts at different levels of SC to make a de…
Anomaly Detection in High Dimensional Data
Priyanga Dilini Talagala, Rob J. Hyndman, Kate Smith-Miles
The HDoutliers algorithm is a powerful unsupervised algorithm for detecting anomalies in high-dimensional data, with a strong theoretical foundation. However, it suffers from some…
GRATIS: GeneRAting TIme Series with diverse and controllable characteristics
Yanfei Kang, Rob J Hyndman, Feng Li
The explosion of time series data in recent years has brought a flourish of new time series analysis methods, for forecasting, clustering, classification and other tasks. The evalu…
A feature-based framework for detecting technical outliers in water-quality data from in situ sensors
Priyanga Dilini Talagala, Rob J. Hyndman, Catherine Leigh +2
Outliers due to technical errors in water-quality data from in situ sensors can reduce data quality and have a direct impact on inference drawn from subsequent data analysis. Howev…
A new tidy data structure to support exploration and modeling of temporal data
Earo Wang, Dianne Cook, Rob J Hyndman
Mining temporal data for information is often inhibited by a multitude of formats: irregular or multiple time intervals, point events that need aggregating, multiple observational…