Detecting time series outliers
The tsoutliers() function in the forecast package for R is useful for identifying anomalies in a time series. However, it is not properly documented anywhere. This post is intended to fill that gap. The function began as an answer on CrossValidated and was later added to the forecast package because I thought it might be useful to other people. It has since been updated and made more reliable.Forecasting: Principles and Practice
Recent papers
- Sevvandi Kandanaarachchi, Rob J Hyndman (2021) Leave-one-out kernel density estimates for outlier detection. J Computational & Graphical Statistics, to appear. Abstract pdf code
- Rakshitha Godahewa, Christoph Bergmeir, Geoffrey I Webb, Rob J Hyndman, Pablo Montero-Manso (2021) Monash Time Series Forecasting Archive. NeurIPS 2021 Datasets and Benchmarks. Abstract pdf Online code
- George Athanasopoulos, Rob J Hyndman, Nikolaos Kourentzes, Mitchell O'Hara‑Wild (2021) Probabilistic forecasts using expert judgement: the road to recovery from COVID-19. Journal of Travel Research, to appear. Abstract pdf
- Hansika Hewamalage, Pablo Montero-Manso, Christoph Bergmeir, Rob J Hyndman (2021) A Look at the Evaluation Setup of the M5 Forecasting Competition. Abstract pdf
- Kasun Bandara, Rob J Hyndman, Christoph Bergmeir (2021) MSTL: A Seasonal-Trend Decomposition Algorithm for Time Series with Multiple Seasonal Patterns. Abstract pdf
Recent and upcoming seminars
- Uncertain futures: AAS2021. (3 November 2021) YouTube More info...
- Feasts & fables: Time series analysis using R. (28 September 2021) More info...
- The geometry of forecast reconciliation. (16 September 2021) More info...
- GRATIS: GeneRAting TIme Series with diverse and controllable characteristics. (10 September 2021) YouTube More info...
- Uncertain futures: what can we forecast and when should we give up?. (17 August 2021) YouTube More info...