99 citations · 312 across the 30 of their papers we have counts for
10 papers · 1 filter
MSTL: A Seasonal-Trend Decomposition Algorithm for Time Series with Multiple Seasonal Patterns
Kasun Bandara, Rob J Hyndman, Christoph Bergmeir
The decomposition of time series into components is an important task that helps to understand time series and can enable better forecasting. Nowadays, with high sampling rates lea…
Understanding links between water-quality variables and nitrate concentration in freshwater streams using high-frequency sensor data
Claire Kermorvant, Benoit Liquet, Guy Litt +5
Real time monitoring using in situ sensors is becoming a common approach for measuring water quality within watersheds. High frequency measurements produce big data sets that prese…
Visualizing probability distributions across bivariate cyclic temporal granularities
Sayani Gupta, Rob J Hyndman, Dianne Cook +1
Deconstructing a time index into time granularities can assist in exploration and automated analysis of large temporal data sets. This paper describes classes of time deconstructio…
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…
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…
Predicting Sediment and Nutrient Concentrations in Rivers Using High Frequency Water Quality Surrogates
Catherine Leigh, Sevvandi Kandanaarachchi, James M. McGree +4
A particular focus of water-quality monitoring is the concentrations of sediments and nutrients in rivers, constituents that can smother biota and cause eutrophication. However, th…
Calendar-based graphics for visualizing people's daily schedules
Earo Wang, Dianne Cook, Rob J Hyndman
Calendars are broadly used in society to display temporal information, and events. This paper describes a new R package with functionality to organize and display temporal data, co…
A framework for automated anomaly detection in high frequency water-quality data from in situ sensors
Catherine Leigh, Omar Alsibai, Rob J. Hyndman +9
River water-quality monitoring is increasingly conducted using automated in situ sensors, enabling timelier identification of unexpected values. However, anomalies caused by techni…
Grouped functional time series forecasting: An application to age-specific mortality rates
Han Lin Shang, Rob J Hyndman
Age-specific mortality rates are often disaggregated by different attributes, such as sex, state and ethnicity. Forecasting age-specific mortality rates at the national and sub-nat…